Resolwe Bioinformatics

Bioinformatics pipelines for the Resolwe dataflow package for Django framework.

Contents

Writing processes

A tutorial about writing bioinformatics pipelines (process is a step in the pipeline) is in Resolwe SDK for Python documentation.

Tools

Frequently, it is very useful to write a custom script in Python or R to perform a certain task in process’ algorithm. For an example, see the tutorial in Resolwe SDK for Python documentation.

Custom scripts needed by processes included with Resolwe Bioinformatics are located in the resolwe_bio/tools directory.

Note

A Resolwe’s Flow Executor searches for tools in a Django application’s tools directory or directories specified in the RESOLWE_CUSTOM_TOOLS_PATHS Django setting.

Process catalog

Resolwe Bioinformatics includes over 100 processes. They are organized in categories. The type tree will help process developers with pipeline design. For process details browse process definitions.

Processes by category

Differential expression
Plot

Type tree

Process types are listed alphabetically. Next to each type is a list of processes of that type. Types are hierarchical, with levels of hierarchy separated by colon “:”. The hierarchy defines what is accepted on inputs. For instance, Expression (Cuffnorm) process’ input is data:alignment:bam. This means it also accepts all subtypes (e.g., data:alignment:bam:bwasw, data:alignment:bam:bowtie1 and data:alignment:bam:tophat). We encourage the use of existing types in custom processes.

Process definitions

ATAC-Seq
data:workflow:atacseqworkflow-atac-seq (data:reads:fastq  reads, data:genome:fasta  genome, data:bed  promoter, basic:string  mode, basic:string  speed, basic:boolean  use_se, basic:boolean  discordantly, basic:boolean  rep_se, basic:integer  minins, basic:integer  maxins, basic:integer  trim_5, basic:integer  trim_3, basic:integer  trim_iter, basic:integer  trim_nucl, basic:string  rep_mode, basic:integer  k_reports, basic:integer  q_threshold, basic:integer  n_sub, basic:boolean  tn5, basic:integer  shift, basic:boolean  tagalign, basic:string  duplicates, basic:string  duplicates_prepeak, basic:decimal  qvalue, basic:decimal  pvalue, basic:decimal  pvalue_prepeak, basic:integer  cap_num, basic:integer  mfold_lower, basic:integer  mfold_upper, basic:integer  slocal, basic:integer  llocal, basic:integer  extsize, basic:integer  shift, basic:integer  band_width, basic:boolean  nolambda, basic:boolean  fix_bimodal, basic:boolean  nomodel, basic:boolean  nomodel_prepeak, basic:boolean  down_sample, basic:boolean  bedgraph, basic:boolean  spmr, basic:boolean  call_summits, basic:boolean  broad, basic:decimal  broad_cutoff)[Source: v2.0.2]

This ATAC-seq pipeline closely follows the official ENCODE DCC pipeline. It is comprised of three steps; alignment, pre-peakcall QC, and calling peaks (with post-peakcall QC). First, reads are aligned to a genome using [Bowtie2](http://bowtie-bio.sourceforge.net/index.shtml) aligner. Next, pre-peakcall QC metrics are calculated. QC report contains ENCODE 3 proposed QC metrics – [NRF](https://www.encodeproject.org/data-standards/terms/), [PBC bottlenecking coefficients, NSC, and RSC](https://genome.ucsc.edu/ENCODE/qualityMetrics.html#chipSeq). Finally, the peaks are called using [MACS2](https://github.com/taoliu/MACS/). The post-peakcall QC report includes additional QC metrics – number of peaks, fraction of reads in peaks (FRiP), number of reads in peaks, and if promoter regions BED file is provided, number of reads in promoter regions, fraction of reads in promoter regions, number of peaks in promoter regions, and fraction of reads in promoter regions.

Input arguments

reads
label:Select sample(s)
type:data:reads:fastq
genome
label:Genome
type:data:genome:fasta
promoter
label:Promoter regions BED file
type:data:bed
description:BED file containing promoter regions (TSS+-1000bp for example). Needed to get the number of peaks and reads mapped to promoter regions.
required:False
alignment.mode
label:Alignment mode
type:basic:string
description:End to end: Bowtie 2 requires that the entire read align from one end to the other, without any trimming (or “soft clipping”) of characters from either end. Local: Bowtie 2 does not require that the entire read align from one end to the other. Rather, some characters may be omitted (“soft clipped”) from the ends in order to achieve the greatest possible alignment score.
default:--local
choices:
  • end to end mode: --end-to-end
  • local: --local
alignment.speed
label:Speed vs. Sensitivity
type:basic:string
default:--sensitive
choices:
  • Very fast: --very-fast
  • Fast: --fast
  • Sensitive: --sensitive
  • Very sensitive: --very-sensitive
alignment.PE_options.use_se
label:Map as single-ended (for paired-end reads only)
type:basic:boolean
description:If this option is selected paired-end reads will be mapped as single-ended and other paired-end options are ignored.
default:False
alignment.PE_options.discordantly
label:Report discordantly matched read
type:basic:boolean
description:If both mates have unique alignments, but the alignments do not match paired-end expectations (orientation and relative distance) then alignment will be reported. Useful for detecting structural variations.
default:True
alignment.PE_options.rep_se
label:Report single ended
type:basic:boolean
description:If paired alignment can not be found Bowtie2 tries to find alignments for the individual mates.
default:True
alignment.PE_options.minins
label:Minimal distance
type:basic:integer
description:The minimum fragment length for valid paired-end alignments. 0 imposes no minimum.
default:0
alignment.PE_options.maxins
label:Maximal distance
type:basic:integer
description:The maximum fragment length for valid paired-end alignments.
default:2000
alignment.start_trimming.trim_5
label:Bases to trim from 5’
type:basic:integer
description:Number of bases to trim from from 5’ (left) end of each read before alignment.
default:0
alignment.start_trimming.trim_3
label:Bases to trim from 3’
type:basic:integer
description:Number of bases to trim from from 3’ (right) end of each read before alignment
default:0
alignment.trimming.trim_iter
label:Iterations
type:basic:integer
description:Number of iterations.
default:0
alignment.trimming.trim_nucl
label:Bases to trim
type:basic:integer
description:Number of bases to trim from 3’ end in each iteration.
default:2
alignment.reporting.rep_mode
label:Report mode
type:basic:string
description:Default mode: search for multiple alignments, report the best one; -k mode: search for one or more alignments, report each; -a mode: search for and report all alignments
default:def
choices:
  • Default mode: def
  • -k mode: k
  • -a mode (very slow): a
alignment.reporting.k_reports
label:Number of reports (for -k mode only)
type:basic:integer
description:Searches for at most X distinct, valid alignments for each read. The search terminates when it can’t find more distinct valid alignments, or when it finds X, whichever happens first.
default:5
prepeakqc_settings.q_threshold
label:Quality filtering threshold
type:basic:integer
default:30
prepeakqc_settings.n_sub
label:Number of reads to subsample
type:basic:integer
default:25000000
prepeakqc_settings.tn5
label:TN5 shifting
type:basic:boolean
description:Tn5 transposon shifting. Shift reads on “+” strand by 4bp and reads on “-” strand by 5bp.
default:True
prepeakqc_settings.shift
label:User-defined cross-correlation peak strandshift
type:basic:integer
description:If defined, SPP tool will not try to estimate fragment length but will use the given value as fragment length.
default:0
settings.tagalign
label:Use tagAlign files
type:basic:boolean
description:Use filtered tagAlign files as case (treatment) and control (background) samples. If extsize parameter is not set, run MACS using input’s estimated fragment length.
default:True
settings.duplicates
label:Number of duplicates
type:basic:string
description:It controls the MACS behavior towards duplicate tags at the exact same location – the same coordination and the same strand. The ‘auto’ option makes MACS calculate the maximum tags at the exact same location based on binomal distribution using 1e-5 as pvalue cutoff and the ‘all’ option keeps all the tags. If an integer is given, at most this number of tags will be kept at the same location. The default is to keep one tag at the same location.
required:False
hidden:settings.tagalign
choices:
  • 1: 1
  • auto: auto
  • all: all
settings.duplicates_prepeak
label:Number of duplicates
type:basic:string
description:It controls the MACS behavior towards duplicate tags at the exact same location – the same coordination and the same strand. The ‘auto’ option makes MACS calculate the maximum tags at the exact same location based on binomal distribution using 1e-5 as pvalue cutoff and the ‘all’ option keeps all the tags. If an integer is given, at most this number of tags will be kept at the same location. The default is to keep one tag at the same location.
required:False
hidden:!settings.tagalign
default:all
choices:
  • 1: 1
  • auto: auto
  • all: all
settings.qvalue
label:Q-value cutoff
type:basic:decimal
description:The q-value (minimum FDR) cutoff to call significant regions. Q-values are calculated from p-values using Benjamini-Hochberg procedure.
required:False
disabled:settings.pvalue && settings.pvalue_prepeak
settings.pvalue
label:P-value cutoff
type:basic:decimal
description:The p-value cutoff. If specified, MACS2 will use p-value instead of q-value cutoff.
required:False
disabled:settings.qvalue
hidden:settings.tagalign
settings.pvalue_prepeak
label:P-value cutoff
type:basic:decimal
description:The p-value cutoff. If specified, MACS2 will use p-value instead of q-value cutoff.
disabled:settings.qvalue
hidden:!settings.tagalign || settings.qvalue
default:0.01
settings.cap_num
label:Cap number of peaks by taking top N peaks
type:basic:integer
description:To keep all peaks set value to 0.
disabled:settings.broad
default:300000
settings.mfold_lower
label:MFOLD range (lower limit)
type:basic:integer
description:This parameter is used to select the regions within MFOLD range of high-confidence enrichment ratio against background to build model. The regions must be lower than upper limit, and higher than the lower limit of fold enrichment. DEFAULT:10,30 means using all regions not too low (>10) and not too high (<30) to build paired-peaks model. If MACS can not find more than 100 regions to build model, it will use the –extsize parameter to continue the peak detection ONLY if –fix-bimodal is set.
required:False
settings.mfold_upper
label:MFOLD range (upper limit)
type:basic:integer
description:This parameter is used to select the regions within MFOLD range of high-confidence enrichment ratio against background to build model. The regions must be lower than upper limit, and higher than the lower limit of fold enrichment. DEFAULT:10,30 means using all regions not too low (>10) and not too high (<30) to build paired-peaks model. If MACS can not find more than 100 regions to build model, it will use the –extsize parameter to continue the peak detection ONLY if –fix-bimodal is set.
required:False
settings.slocal
label:Small local region
type:basic:integer
description:Slocal and llocal parameters control which two levels of regions will be checked around the peak regions to calculate the maximum lambda as local lambda. By default, MACS considers 1000bp for small local region (–slocal), and 10000bps for large local region (–llocal) which captures the bias from a long range effect like an open chromatin domain. You can tweak these according to your project. Remember that if the region is set too small, a sharp spike in the input data may kill the significant peak.
required:False
settings.llocal
label:Large local region
type:basic:integer
description:Slocal and llocal parameters control which two levels of regions will be checked around the peak regions to calculate the maximum lambda as local lambda. By default, MACS considers 1000bp for small local region (–slocal), and 10000bps for large local region (–llocal) which captures the bias from a long range effect like an open chromatin domain. You can tweak these according to your project. Remember that if the region is set too small, a sharp spike in the input data may kill the significant peak.
required:False
settings.extsize
label:extsize
type:basic:integer
description:While ‘–nomodel’ is set, MACS uses this parameter to extend reads in 5’->3’ direction to fix-sized fragments. For example, if the size of binding region for your transcription factor is 200 bp, and you want to bypass the model building by MACS, this parameter can be set as 200. This option is only valid when –nomodel is set or when MACS fails to build model and –fix-bimodal is on.
default:150
settings.shift
label:Shift
type:basic:integer
description:Note, this is NOT the legacy –shiftsize option which is replaced by –extsize! You can set an arbitrary shift in bp here. Please Use discretion while setting it other than default value (0). When –nomodel is set, MACS will use this value to move cutting ends (5’) then apply –extsize from 5’ to 3’ direction to extend them to fragments. When this value is negative, ends will be moved toward 3’->5’ direction, otherwise 5’->3’ direction. Recommended to keep it as default 0 for ChIP-Seq datasets, or -1 * half of EXTSIZE together with –extsize option for detecting enriched cutting loci such as certain DNAseI-Seq datasets. Note, you can’t set values other than 0 if format is BAMPE for paired-end data. Default is 0.
default:-75
settings.band_width
label:Band width
type:basic:integer
description:The band width which is used to scan the genome ONLY for model building. You can set this parameter as the sonication fragment size expected from wet experiment. The previous side effect on the peak detection process has been removed. So this parameter only affects the model building.
required:False
settings.nolambda
label:Use backgroud lambda as local lambda
type:basic:boolean
description:With this flag on, MACS will use the background lambda as local lambda. This means MACS will not consider the local bias at peak candidate regions.
default:False
settings.fix_bimodal
label:Turn on the auto paired-peak model process
type:basic:boolean
description:Whether turn on the auto paired-peak model process. If it’s set, when MACS failed to build paired model, it will use the nomodel settings, the ‘–extsize’ parameter to extend each tags. If set, MACS will be terminated if paired-peak model is failed.
default:False
settings.nomodel
label:Bypass building the shifting model
type:basic:boolean
description:While on, MACS will bypass building the shifting model.
hidden:settings.tagalign
default:False
settings.nomodel_prepeak
label:Bypass building the shifting model
type:basic:boolean
description:While on, MACS will bypass building the shifting model.
hidden:!settings.tagalign
default:True
settings.down_sample
label:Down-sample
type:basic:boolean
description:When set, random sampling method will scale down the bigger sample. By default, MACS uses linear scaling. This option will make the results unstable and irreproducible since each time, random reads would be selected, especially the numbers (pileup, pvalue, qvalue) would change. Consider to use ‘randsample’ script before MACS2 runs instead.
default:False
settings.bedgraph
label:Save fragment pileup and control lambda
type:basic:boolean
description:If this flag is on, MACS will store the fragment pileup, control lambda, -log10pvalue and -log10qvalue scores in bedGraph files. The bedGraph files will be stored in current directory named NAME+’_treat_pileup.bdg’ for treatment data, NAME+’_control_lambda.bdg’ for local lambda values from control, NAME+’_treat_pvalue.bdg’ for Poisson pvalue scores (in -log10(pvalue) form), and NAME+’_treat_qvalue.bdg’ for q-value scores from Benjamini-Hochberg-Yekutieli procedure.
default:True
settings.spmr
label:Save signal per million reads for fragment pileup profiles
type:basic:boolean
disabled:settings.bedgraph === false
default:True
settings.call_summits
label:Call summits
type:basic:boolean
description:MACS will now reanalyze the shape of signal profile (p or q-score depending on cutoff setting) to deconvolve subpeaks within each peak called from general procedure. It’s highly recommended to detect adjacent binding events. While used, the output subpeaks of a big peak region will have the same peak boundaries, and different scores and peak summit positions.
default:True
settings.broad
label:Composite broad regions
type:basic:boolean
description:When this flag is on, MACS will try to composite broad regions in BED12 (a gene-model-like format) by putting nearby highly enriched regions into a broad region with loose cutoff. The broad region is controlled by another cutoff through –broad-cutoff. The maximum length of broad region length is 4 times of d from MACS.
disabled:settings.call_summits === true
default:False
settings.broad_cutoff
label:Broad cutoff
type:basic:decimal
description:Cutoff for broad region. This option is not available unless –broad is set. If -p is set, this is a p-value cutoff, otherwise, it’s a q-value cutoff. DEFAULT = 0.1
required:False
disabled:settings.call_summits === true || settings.broad !== true

Output results

Abstract alignment process
data:alignmentabstract-alignment ()[Source: v1.0.0]

Input arguments

Output results

bam
label:Alignment file
type:basic:file
bai
label:Alignment index BAI
type:basic:file
species
label:Species
type:basic:string
build
label:Build
type:basic:string
Abstract annotation process
data:annotationabstract-annotation ()[Source: v1.0.0]

Input arguments

Output results

annot
label:Uploaded file
type:basic:file
source
label:Gene ID source
type:basic:string
species
label:Species
type:basic:string
build
label:Build
type:basic:string
Abstract bed process
data:bedabstract-bed ()[Source: v1.0.0]

Input arguments

Output results

bed
label:BED
type:basic:file
species
label:Species
type:basic:string
build
label:Build
type:basic:string
Abstract differential expression process
data:differentialexpressionabstract-differentialexpression ()[Source: v1.0.0]

Input arguments

Output results

raw
label:Differential expression (gene level)
type:basic:file
de_json
label:Results table (JSON)
type:basic:json
de_file
label:Results table (file)
type:basic:file
source
label:Gene ID source
type:basic:string
species
label:Species
type:basic:string
build
label:Build
type:basic:string
feature_type
label:Feature type
type:basic:string
Abstract expression process
data:expressionabstract-expression ()[Source: v1.0.0]

Input arguments

Output results

exp
label:Normalized expression
type:basic:file
rc
label:Read counts
type:basic:file
required:False
exp_json
label:Expression (json)
type:basic:json
exp_type
label:Expression type
type:basic:string
source
label:Gene ID source
type:basic:string
species
label:Species
type:basic:string
build
label:Build
type:basic:string
feature_type
label:Feature type
type:basic:string
Accel Amplicon Pipeline
data:workflow:ampliconworkflow-accel (data:reads:fastq:paired  reads, data:genome:fasta  genome, data:masterfile:amplicon  master_file, data:seq:nucleotide  adapters, list:data:variants:vcf  known_indels, list:data:variants:vcf  known_vars, data:variants:vcf  dbsnp, basic:integer  mbq, basic:integer  stand_call_conf, basic:integer  min_bq, basic:integer  min_alt_bq, list:data:variants:vcf  known_vars_db, basic:decimal  af_threshold)[Source: v4.0.1]

Processing pipeline to analyse the Accel-Amplicon NGS panel data. The raw amplicon sequencing reads are quality trimmed using Trimmomatic. The quality of the raw and trimmed data is assesed using the FASTQC tool. Quality trimmed reads are aligned to a reference genome using BWA mem. Sequencing primers are removed from the aligned reads using Primerclip. Amplicon performance stats are calculated using Bedtools coveragebed and Picard CollectTargetedPcrMetrics programs. Prior to variant calling, the alignment file is preprocessed using the GATK IndelRealigner and BaseRecalibrator tools. GATK HaplotypeCaller and Lofreq tools are used to call germline variants. Called variants are annotated using the SnpEff tool. Finally, the amplicon performance metrics and identified variants data are used to generate the PDF analysis report.

Input arguments

reads
label:Input reads
type:data:reads:fastq:paired
genome
label:Genome
type:data:genome:fasta
master_file
label:Experiment Master file
type:data:masterfile:amplicon
adapters
label:Adapters
type:data:seq:nucleotide
description:Provide an Illumina sequencing adapters file (.fasta) with adapters to be removed by Trimmomatic.
preprocess_bam.known_indels
label:Known indels
type:list:data:variants:vcf
preprocess_bam.known_vars
label:Known variants
type:list:data:variants:vcf
gatk.dbsnp
label:dbSNP
type:data:variants:vcf
gatk.mbq
label:Min Base Quality
type:basic:integer
description:Minimum base quality required to consider a base for calling.
default:20
gatk.stand_call_conf
label:Min call confidence threshold
type:basic:integer
description:The minimum phred-scaled confidence threshold at which variants should be called.
default:20
lofreq.min_bq
label:Min baseQ
type:basic:integer
description:Skip any base with baseQ smaller than the default value.
default:20
lofreq.min_alt_bq
label:Min alternate baseQ
type:basic:integer
description:Skip alternate bases with baseQ smaller than the default value.
default:20
var_annot.known_vars_db
label:Known variants
type:list:data:variants:vcf
report.af_threshold
label:Allele frequency threshold
type:basic:decimal
default:0.01

Output results

Align (BWA) and trim adapters
data:alignment:bam:bwatrimalign-bwa-trim (data:masterfile:amplicon  master_file, data:genome:fasta  genome, data:reads:fastq  reads, basic:integer  seed_l, basic:integer  band_w, basic:decimal  re_seeding, basic:boolean  m, basic:integer  match, basic:integer  missmatch, basic:integer  gap_o, basic:integer  gap_e, basic:integer  clipping, basic:integer  unpaired_p, basic:boolean  report_all, basic:integer  report_tr)[Source: v1.2.2]

Align with BWA mem and trim the sam output. The process uses the memory-optimized Primertrim tool.

Input arguments

master_file
label:Master file
type:data:masterfile:amplicon
description:Amplicon experiment design file that holds the information about the primers to be removed.
genome
label:Reference genome
type:data:genome:fasta
reads
label:Reads
type:data:reads:fastq
seed_l
label:Minimum seed length
type:basic:integer
description:Minimum seed length. Matches shorter than minimum seed length will be missed. The alignment speed is usually insensitive to this value unless it significantly deviates 20.
default:19
band_w
label:Band width
type:basic:integer
description:Gaps longer than this will not be found.
default:100
re_seeding
label:Re-seeding factor
type:basic:decimal
description:Trigger re-seeding for a MEM longer than minSeedLen*FACTOR. This is a key heuristic parameter for tuning the performance. Larger value yields fewer seeds, which leads to faster alignment speed but lower accuracy.
default:1.5
m
label:Mark shorter split hits as secondary
type:basic:boolean
description:Mark shorter split hits as secondary (for Picard compatibility)
default:False
scoring.match
label:Score of a match
type:basic:integer
default:1
scoring.missmatch
label:Mismatch penalty
type:basic:integer
default:4
scoring.gap_o
label:Gap open penalty
type:basic:integer
default:6
scoring.gap_e
label:Gap extension penalty
type:basic:integer
default:1
scoring.clipping
label:Clipping penalty
type:basic:integer
description:Clipping is applied if final alignment score is smaller than (best score reaching the end of query) - (Clipping penalty)
default:5
scoring.unpaired_p
label:Penalty for an unpaired read pair
type:basic:integer
description:Affinity to force pair. Score: scoreRead1+scoreRead2-Penalty
default:9
reporting.report_all
label:Report all found alignments
type:basic:boolean
description:Output all found alignments for single-end or unpaired paired-end reads. These alignments will be flagged as secondary alignments.
default:False
reporting.report_tr
label:Report threshold score
type:basic:integer
description:Don’t output alignment with score lower than defined number. This option only affects output.
default:30

Output results

bam
label:Alignment file
type:basic:file
description:Position sorted alignment
bai
label:Index BAI
type:basic:file
stats
label:Statistics
type:basic:file
bigwig
label:BigWig file
type:basic:file
required:False
species
label:Species
type:basic:string
build
label:Build
type:basic:string
Amplicon report
data:report:ampliconamplicon-report (data:picard:coverage  pcr_metrics, data:coverage  coverage, data:masterfile:amplicon  master_file, list:data:snpeff  annot_vars, basic:decimal  af_threshold)[Source: v1.0.4]

Create amplicon report.

Input arguments

pcr_metrics
label:Picard TargetedPcrMetrics
type:data:picard:coverage
coverage
label:Coverage
type:data:coverage
master_file
label:Amplicon master file
type:data:masterfile:amplicon
annot_vars
label:Annotated variants (snpEff)
type:list:data:snpeff
af_threshold
label:Allele frequency threshold
type:basic:decimal
default:0.01

Output results

report
label:Report
type:basic:file
panel_name
label:Panel name
type:basic:string
stats
label:File with sample statistics
type:basic:file
amplicon_cov
label:Amplicon coverage file (nomergebed)
type:basic:file
variant_tables
label:Variant tabels (snpEff)
type:list:basic:file
Amplicon table
data:varianttable:ampliconamplicon-table (data:masterfile:amplicon  master_file, data:coverage  coverage, list:data:snpeff  annot_vars, basic:boolean  all_amplicons, basic:string  table_name)[Source: v1.0.1]

Create variant table for use together with the genome browser.

Input arguments

master_file
label:Master file
type:data:masterfile:amplicon
coverage
label:Amplicon coverage
type:data:coverage
annot_vars
label:Annotated variants
type:list:data:snpeff
all_amplicons
label:Report all amplicons
type:basic:boolean
default:False
table_name
label:Amplicon table name
type:basic:string
default:Amplicons containing variants

Output results

variant_table
label:Variant table
type:basic:json
Annotate novel splice junctions (regtools)
data:junctions:regtoolsregtools-junctions-annotate (data:genome:fasta  genome, data:annotation:gtf  annotation, data:alignment:bam:star  alignment_star, data:alignment:bam  alignment, data:bed  input_bed_junctions)[Source: v0.2.1]

Identify novel splice junctions by using regtools to annotate against a reference. The process accepts reference genome, reference genome annotation (GTF), and input with reads information (STAR aligment or reads aligned by any other aligner or junctions in BED12 format). If STAR aligner data is given as input, the process calculates BED12 file from STAR ‘SJ.out.tab’ file, and annotates all junctions with ‘regtools junctions annotate’ command. When reads are aligned by other aligner, junctions are extracted with ‘regtools junctions extract’ tool and then annotated with ‘junction annotate’ command. Third option allows user to provide directly BED12 file with junctions, which are then annotated. Finnally, annotated novel junctions are filtered in a separate output file. More information can be found in the [regtools manual](https://regtools.readthedocs.io/en/latest/).

Input arguments

genome
label:Reference genome
type:data:genome:fasta
annotation
label:Reference genome annotation (GTF)
type:data:annotation:gtf
alignment_star
label:STAR alignment
type:data:alignment:bam:star
description:Splice junctions detected by STAR aligner (SJ.out.tab STAR output file). Please provide one input ‘STAR alignment’ or ‘Alignment’ by any aligner or directly ‘Junctions in BED12 format’.
required:False
alignment
label:Alignment
type:data:alignment:bam
description:Aligned reads from which splice junctions are going to be extracted. Please provide one input ‘STAR alignment’ or ‘Alignment’ by any aligner or directly ‘Junctions in BED12 format’.
required:False
input_bed_junctions
label:Junctions in BED12 format
type:data:bed
description:Splice junctions in BED12 format. Please provide one input ‘STAR alignment’ or ‘Alignment’ by any aligner or directly ‘Junctions in BED12 format’.
required:False

Output results

novel_splice_junctions
label:Table of annotated novel splice junctions
type:basic:file
splice_junctions
label:Table of annotated splice junctions
type:basic:file
novel_sj_bed
label:Novel splice junctions in BED format
type:basic:file
bed
label:Splice junctions in BED format
type:basic:file
novel_sj_bigbed_igv_ucsc
label:Novel splice junctions in BigBed format
type:basic:file
required:False
bigbed_igv_ucsc
label:Splice junctions in BigBed format
type:basic:file
required:False
novel_sj_tbi_jbrowse
label:Novel splice junctions bed tbi index for JBrowse
type:basic:file
tbi_jbrowse
label:Bed tbi index for JBrowse
type:basic:file
species
label:Species
type:basic:string
build
label:Build
type:basic:string
Archive and make multi-sample report for amplicon data
data:archive:samples:ampliconamplicon-archive-multi-report (list:data  data, list:basic:string  fields, basic:boolean  j)[Source: v0.2.5]

Create an archive of output files. The ouput folder structure is organized by sample slug and data object’s output-field names. Additionally, create multi-sample report for selected samples.

Input arguments

data
label:Data list
type:list:data
fields
label:Output file fields
type:list:basic:string
j
label:Junk paths
type:basic:boolean
description:Store just names of saved files (junk the path)
default:False

Output results

archive
label:Archive of selected samples and a heatmap comparing them
type:basic:file
Archive samples
data:archive:samplesarchive-samples (list:data  data, list:basic:string  fields, basic:boolean  j)[Source: v0.2.3]

Create an archive of output files. The ouput folder structure is organized by sample slug and data object’s output-field names.

Input arguments

data
label:Data list
type:list:data
fields
label:Output file fields
type:list:basic:string
j
label:Junk paths
type:basic:boolean
description:Store just names of saved files (junk the path)
default:False

Output results

archive
label:Archive
type:basic:file
BAM file
data:alignment:bam:uploadupload-bam (basic:file  src, basic:string  species, basic:string  build)[Source: v1.4.1]

Import a BAM file (.bam), which is the binary format for storing sequence alignment data. This format is described on the [SAM Tools web site](http://samtools.github.io/hts-specs/).

Input arguments

src
label:Mapping (BAM)
type:basic:file
description:A mapping file in BAM format. The file will be indexed on upload, so additional BAI files are not required.
validate_regex:\.(bam)$
species
label:Species
type:basic:string
description:Species latin name.
choices:
  • Homo sapiens: Homo sapiens
  • Mus musculus: Mus musculus
  • Rattus norvegicus: Rattus norvegicus
  • Dictyostelium discoideum: Dictyostelium discoideum
  • Odocoileus virginianus texanus: Odocoileus virginianus texanus
  • Solanum tuberosum: Solanum tuberosum
build
label:Build
type:basic:string

Output results

bam
label:Uploaded file
type:basic:file
bai
label:Index BAI
type:basic:file
stats
label:Alignment statistics
type:basic:file
bigwig
label:BigWig file
type:basic:file
required:False
species
label:Species
type:basic:string
build
label:Build
type:basic:string
BAM file and index
data:alignment:bam:uploadupload-bam-indexed (basic:file  src, basic:file  src2, basic:string  species, basic:string  build)[Source: v1.4.1]

Import a BAM file (.bam) and BAM index (.bam.bai). BAM file is the binary format for storing sequence alignment data. This format is described on the [SAM Tools web site](http://samtools.github.io/hts-specs/).

Input arguments

src
label:Mapping (BAM)
type:basic:file
description:A mapping file in BAM format.
validate_regex:\.(bam)$
src2
label:bam index (*.bam.bai file)
type:basic:file
description:An index file of a BAM mapping file (ending with bam.bai).
validate_regex:\.(bam.bai)$
species
label:Species
type:basic:string
description:Species latin name.
choices:
  • Homo sapiens: Homo sapiens
  • Mus musculus: Mus musculus
  • Rattus norvegicus: Rattus norvegicus
  • Dictyostelium discoideum: Dictyostelium discoideum
  • Odocoileus virginianus texanus: Odocoileus virginianus texanus
  • Solanum tuberosum: Solanum tuberosum
build
label:Build
type:basic:string

Output results

bam
label:Uploaded file
type:basic:file
bai
label:Index BAI
type:basic:file
stats
label:Alignment statistics
type:basic:file
bigwig
label:BigWig file
type:basic:file
required:False
species
label:Species
type:basic:string
build
label:Build
type:basic:string
BBDuk (paired-end)
data:reads:fastq:paired:bbdukbbduk-paired (data:reads:fastq:paired  reads, basic:integer  min_length, basic:boolean  show_advanced, list:data:seq:nucleotide  sequences, list:basic:string  literal_sequences, basic:integer  kmer_length, basic:boolean  check_reverse_complements, basic:boolean  mask_middle_base, basic:integer  min_kmer_hits, basic:decimal  min_kmer_fraction, basic:decimal  min_coverage_fraction, basic:integer  hamming_distance, basic:integer  query_hamming_distance, basic:integer  edit_distance, basic:integer  hamming_distance2, basic:integer  query_hamming_distance2, basic:integer  edit_distance2, basic:boolean  forbid_N, basic:boolean  remove_if_either_bad, basic:boolean  find_best_match, basic:boolean  perform_error_correction, basic:string  k_trim, basic:string  k_mask, basic:boolean  mask_fully_covered, basic:integer  min_k, basic:string  quality_trim, basic:integer  trim_quality, basic:integer  trim_poly_A, basic:decimal  min_length_fraction, basic:integer  max_length, basic:integer  min_average_quality, basic:integer  min_average_quality_bases, basic:integer  min_base_quality, basic:integer  min_consecutive_bases, basic:integer  trim_pad, basic:boolean  trim_by_overlap, basic:boolean  strict_overlap, basic:integer  min_overlap, basic:integer  min_insert, basic:boolean  trim_pairs_evenly, basic:integer  force_trim_left, basic:integer  force_trim_right, basic:integer  force_trim_right2, basic:integer  force_trim_mod, basic:integer  restrict_left, basic:integer  restrict_right, basic:decimal  min_GC, basic:decimal  max_GC, basic:integer  maxns, basic:boolean  toss_junk, basic:boolean  chastity_filter, basic:boolean  barcode_filter, list:data:seq:nucleotide  barcode_files, list:basic:string  barcode_sequences, basic:integer  x_min, basic:integer  y_min, basic:integer  x_max, basic:integer  y_max, basic:decimal  entropy, basic:integer  entropy_window, basic:integer  entropy_k, basic:boolean  entropy_mask, basic:integer  min_base_frequency, basic:boolean  nogroup)[Source: v2.2.2]

BBDuk combines the most common data-quality-related trimming, filtering, and masking operations into a single high-performance tool. It is capable of quality-trimming and filtering, adapter-trimming, contaminant-filtering via kmer matching, sequence masking, GC-filtering, length filtering, entropy-filtering, format conversion, histogram generation, subsampling, quality-score recalibration, kmer cardinality estimation, and various other operations in a single pass. See [here](https://jgi.doe.gov/data-and-tools/bbtools/bb-tools-user-guide/bbduk-guide/) for more information.

Input arguments

reads
label:Reads
type:data:reads:fastq:paired
min_length
label:Minimum length [minlength=10]
type:basic:integer
description:Reads shorter than the minimum length will be discarded after trimming.
default:10
show_advanced
label:Show advanced parameters
type:basic:boolean
default:False
reference.sequences
label:Sequences [ref]
type:list:data:seq:nucleotide
description:Reference sequences include adapters, contaminants, and degenerate sequences. They can be provided in a multi-sequence FASTA file or as a set of literal sequences below.
required:False
reference.literal_sequences
label:Literal sequences [literal]
type:list:basic:string
description:Literal sequences can be specified by inputting them one by one and pressing Enter after each sequence.
required:False
default:[]
processing.kmer_length
label:Kmer length [k=27]
type:basic:integer
description:Kmer length used for finding contaminants. Contaminants shorter than kmer length will not be found. Kmer length must be at least 1.
default:27
processing.check_reverse_complements
label:Look for reverse complements of kmers in addition to forward kmers [rcomp=t]
type:basic:boolean
default:True
processing.mask_middle_base
label:Treat the middle base of a kmer as a wildcard to increase sensitivity in the presence of errors [maskmiddle=t]
type:basic:boolean
default:True
processing.min_kmer_hits
label:Minimum number of kmer hits [minkmerhits=1]
type:basic:integer
description:Reads need at least this many matching kmers to be considered as matching the reference.
default:1
processing.min_kmer_fraction
label:Minimum kmer fraction [minkmerfraction=0.0]
type:basic:decimal
description:A read needs at least this fraction of its total kmers to hit a reference in order to be considered a match. If this and ‘Minimum number of kmer hits’ are set, the greater is used.
default:0.0
processing.min_coverage_fraction
label:Minimum coverage fraction [mincovfraction=0.0]
type:basic:decimal
description:A read needs at least this fraction of its total bases to be covered by reference kmers to be considered a match. If specified, ‘Minimum coverage fraction’ overrides ‘Minimum number of kmer hits’ and ‘Minimum kmer fraction’.
default:0.0
processing.hamming_distance
label:Maximum Hamming distance for kmers (substitutions only) [hammingdistance=0]
type:basic:integer
default:0
processing.query_hamming_distance
label:Hamming distance for query kmers [qhdist=0]
type:basic:integer
default:0
processing.edit_distance
label:Maximum edit distance from reference kmers (substitutions and indels) [editdistance=0]
type:basic:integer
default:0
processing.hamming_distance2
label:Hamming distance for short kmers when looking for shorter kmers [hammingdistance2=0]
type:basic:integer
default:0
processing.query_hamming_distance2
label:Hamming distance for short query kmers when looking for shorter kmers [qhdist2=0]
type:basic:integer
default:0
processing.edit_distance2
label:Maximum edit distance from short reference kmers (substitutions and indels) when looking for shorter kmers [editdistance2=0]
type:basic:integer
default:0
processing.forbid_N
label:Forbid matching of read kmers containing N [forbidn=f]
type:basic:boolean
description:By default, these will match a reference ‘A’ if ‘Maximum Hamming distance for kmers’ > 0 or ‘Maximum edit distance from reference kmers’ > 0, to increase sensitivity.
default:False
processing.remove_if_either_bad
label:Remove both sequences of a paired-end read, if either of them is to be removed [removeifeitherbad=t]
type:basic:boolean
default:True
processing.find_best_match
label:If multiple matches, associate read with sequence sharing most kmers [findbestmatch=t]
type:basic:boolean
default:True
processing.perform_error_correction
label:Perform error correction with BBMerge prior to kmer operations [ecco=f]
type:basic:boolean
default:False
operations.k_trim
label:Trimming protocol to remove bases matching reference kmers from reads [ktrim=f]
type:basic:string
default:f
choices:
  • Don’t trim: f
  • Trim to the right: r
  • Trim to the left: l
operations.k_mask
label:Symbol to replace bases matching reference kmers [kmask=f]
type:basic:string
description:Allows any non-whitespace character other than t or f. Processes short kmers on both ends.
default:f
operations.mask_fully_covered
label:Only mask bases that are fully covered by kmers [maskfullycovered=f]
type:basic:boolean
default:False
operations.min_k
label:Look for shorter kmers at read tips down to this length when k-trimming or masking [mink=0]
type:basic:integer
description:-1 means disabled. Enabling this will disable treating the middle base of a kmer as a wildcard to increase sensitivity in the presence of errors.
default:-1
operations.quality_trim
label:Trimming protocol to remove bases with quality below the minimum average region quality from read ends [qtrim=f]
type:basic:string
description:Performed after looking for kmers. If enabled, set also ‘Average quality below which to trim region’.
default:f
choices:
  • Trim neither end: f
  • Trim both ends: rl
  • Trim only right end: r
  • Trim only left end: l
  • Use sliding window: w
operations.trim_quality
label:Average quality below which to trim region [trimq=6]
type:basic:integer
description:Set trimming protocol to enable this parameter.
disabled:operations.quality_trim == ‘f’
default:6
operations.trim_poly_A
label:Minimum length of poly-A or poly-T tails to trim on either end of reads [trimpolya=0]
type:basic:integer
default:0
operations.min_length_fraction
label:Minimum length fraction [mlf=0.0]
type:basic:decimal
description:Reads shorter than this fraction of original length after trimming will be discarded.
default:0.0
operations.max_length
label:Maximum length [maxlength]
type:basic:integer
description:Reads longer than this after trimming will be discarded.
required:False
operations.min_average_quality
label:Minimum average quality [minavgquality=0]
type:basic:integer
description:Reads with average quality (after trimming) below this will be discarded.
default:0
operations.min_average_quality_bases
label:Number of initial bases to calculate minimum average quality from [maqb=0]
type:basic:integer
description:Used only if positive.
default:0
operations.min_base_quality
label:Minimum base quality below which reads are discarded after trimming [minbasequality=0]
type:basic:integer
default:0
operations.min_consecutive_bases
label:Minimum number of consecutive called bases [mcb=0]
type:basic:integer
default:0
operations.trim_pad
label:Number of bases to trim around matching kmers [tp=0]
type:basic:integer
default:0
operations.trim_by_overlap
label:Trim adapters based on where paired-end reads overlap [tbo=f]
type:basic:boolean
default:False
operations.strict_overlap
label:Adjust sensitivity in ‘Trim adapters based on where paired-end reads overlap’ mode [strictoverlap=t]
type:basic:boolean
default:True
operations.min_overlap
label:Minimum number of overlapping bases [minoverlap=14]
type:basic:integer
description:Require this many bases of overlap for detection.
default:14
operations.min_insert
label:Minimum insert size [mininsert=40]
type:basic:integer
description:Require insert size of at least this for overlap. Should be reduced to 16 for small RNA sequencing.
default:40
operations.trim_pairs_evenly
label:Trim both sequences of paired-end reads to the minimum length of either sequence [tpe=f]
type:basic:boolean
default:False
operations.force_trim_left
label:Position from which to trim bases to the left [forcetrimleft=0]
type:basic:integer
default:0
operations.force_trim_right
label:Position from which to trim bases to the right [forcetrimright=0]
type:basic:integer
default:0
operations.force_trim_right2
label:Number of bases to trim from the right end [forcetrimright2=0]
type:basic:integer
default:0
operations.force_trim_mod
label:Modulo to right-trim reads [forcetrimmod=0]
type:basic:integer
description:Trim reads to the largest multiple of modulo.
default:0
operations.restrict_left
label:Number of leftmost bases to look in for kmer matches [restrictleft=0]
type:basic:integer
default:0
operations.restrict_right
label:Number of rightmosot bases to look in for kmer matches [restrictright=0]
type:basic:integer
default:0
operations.min_GC
label:Minimum GC content [mingc=0.0]
type:basic:decimal
description:Discard reads with lower GC content.
default:0.0
operations.max_GC
label:Maximum GC content [maxgc=1.0]
type:basic:decimal
description:Discard reads with higher GC content.
default:1.0
operations.maxns
label:Max Ns after trimming [maxns=-1]
type:basic:integer
description:If non-negative, reads with more Ns than this (after trimming) will be discarded.
default:-1
operations.toss_junk
label:Discard reads with invalid characters as bases [tossjunk=f]
type:basic:boolean
default:False
header_parsing.chastity_filter
label:Discard reads that fail Illumina chastity filtering [chastityfilter=f]
type:basic:boolean
description:Discard reads with id containing ‘ 1:Y:’ or ‘ 2:Y:’.
default:False
header_parsing.barcode_filter
label:Remove reads with unexpected barcodes if barcodes are set, or barcodes containing ‘N’ otherwise [barcodefilter=f]
type:basic:boolean
description:A barcode must be the last part of the read header.
default:False
header_parsing.barcode_files
label:Barcode sequences [barcodes]
type:list:data:seq:nucleotide
required:False
header_parsing.barcode_sequences
label:Literal barcode sequences [barcodes]
type:list:basic:string
description:Literal barcode sequences can be specified by inputting them one by one and pressing Enter after each sequence.
required:False
default:[]
header_parsing.x_min
label:Minimum X coordinate [xmin=-1]
type:basic:integer
description:If positive, discard reads with a smaller X coordinate.
default:-1
header_parsing.y_min
label:Minimum Y coordinate [ymin=-1]
type:basic:integer
description:If positive, discard reads with a smaller Y coordinate.
default:-1
header_parsing.x_max
label:Maximum X coordinate [xmax=-1]
type:basic:integer
description:If positive, discard reads with a larger X coordinate.
default:-1
header_parsing.y_max
label:Maximum Y coordinate [ymax=-1]
type:basic:integer
description:If positive, discard reads with a larger Y coordinate.
default:-1
complexity.entropy
label:Minimum entropy [entropy=-1.0]
type:basic:decimal
description:Set between 0 and 1 to filter reads with entropy below that value. Higher is more stringent.
default:-1.0
complexity.entropy_window
label:Length of sliding window used to calculate entropy [entropywindow=50]
type:basic:integer
description:To use the sliding window set minimum entropy in range between 0.0 and 1.0.
default:50
complexity.entropy_k
label:Length of kmers used to calcuate entropy [entropyk=5]
type:basic:integer
default:5
complexity.entropy_mask
label:Mask low-entropy parts of sequences with N instead of discarding [entropymask=f]
type:basic:boolean
default:False
complexity.min_base_frequency
label:Minimum base frequency [minbasefrequency=0]
type:basic:integer
default:0
fastqc.nogroup
label:Disable grouping of bases for reads >50bp [nogroup]
type:basic:boolean
description:All reports will show data for every base in the read. Using this option will cause fastqc to crash and burn if you use it on really long reads.
default:False

Output results

fastq
label:Remaining upstream reads
type:list:basic:file
fastq2
label:Remaining downstream reads
type:list:basic:file
statistics
label:Statistics
type:list:basic:file
fastqc_url
label:Upstream quality control with FastQC
type:list:basic:file:html
fastqc_url2
label:Downstream quality control with FastQC
type:list:basic:file:html
fastqc_archive
label:Download upstream FastQC archive
type:list:basic:file
fastqc_archive2
label:Download downstream FastQC archive
type:list:basic:file
BBDuk (single-end)
data:reads:fastq:single:bbdukbbduk-single (data:reads:fastq:single  reads, basic:integer  min_length, basic:boolean  show_advanced, list:data:seq:nucleotide  sequences, list:basic:string  literal_sequences, basic:integer  kmer_length, basic:boolean  check_reverse_complements, basic:boolean  mask_middle_base, basic:integer  min_kmer_hits, basic:decimal  min_kmer_fraction, basic:decimal  min_coverage_fraction, basic:integer  hamming_distance, basic:integer  query_hamming_distance, basic:integer  edit_distance, basic:integer  hamming_distance2, basic:integer  query_hamming_distance2, basic:integer  edit_distance2, basic:boolean  forbid_N, basic:boolean  find_best_match, basic:string  k_trim, basic:string  k_mask, basic:boolean  mask_fully_covered, basic:integer  min_k, basic:string  quality_trim, basic:integer  trim_quality, basic:integer  trim_poly_A, basic:decimal  min_length_fraction, basic:integer  max_length, basic:integer  min_average_quality, basic:integer  min_average_quality_bases, basic:integer  min_base_quality, basic:integer  min_consecutive_bases, basic:integer  trim_pad, basic:integer  min_overlap, basic:integer  min_insert, basic:integer  force_trim_left, basic:integer  force_trim_right, basic:integer  force_trim_right2, basic:integer  force_trim_mod, basic:integer  restrict_left, basic:integer  restrict_right, basic:decimal  min_GC, basic:decimal  max_GC, basic:integer  maxns, basic:boolean  toss_junk, basic:boolean  chastity_filter, basic:boolean  barcode_filter, list:data:seq:nucleotide  barcode_files, list:basic:string  barcode_sequences, basic:integer  x_min, basic:integer  y_min, basic:integer  x_max, basic:integer  y_max, basic:decimal  entropy, basic:integer  entropy_window, basic:integer  entropy_k, basic:boolean  entropy_mask, basic:integer  min_base_frequency, basic:boolean  nogroup)[Source: v2.2.2]

BBDuk combines the most common data-quality-related trimming, filtering, and masking operations into a single high-performance tool. It is capable of quality-trimming and filtering, adapter-trimming, contaminant-filtering via kmer matching, sequence masking, GC-filtering, length filtering, entropy-filtering, format conversion, histogram generation, subsampling, quality-score recalibration, kmer cardinality estimation, and various other operations in a single pass. See [here](https://jgi.doe.gov/data-and-tools/bbtools/bb-tools-user-guide/bbduk-guide/) for more information.

Input arguments

reads
label:Reads
type:data:reads:fastq:single
min_length
label:Minimum length [minlength=10]
type:basic:integer
description:Reads shorter than the minimum length will be discarded after trimming.
default:10
show_advanced
label:Show advanced parameters
type:basic:boolean
default:False
reference.sequences
label:Sequences [ref]
type:list:data:seq:nucleotide
description:Reference sequences include adapters, contaminants, and degenerate sequences. They can be provided in a multi-sequence FASTA file or as a set of literal sequences below.
required:False
reference.literal_sequences
label:Literal sequences [literal]
type:list:basic:string
description:Literal sequences can be specified by inputting them one by one and pressing Enter after each sequence.
required:False
default:[]
processing.kmer_length
label:Kmer length [k=27]
type:basic:integer
description:Kmer length used for finding contaminants. Contaminants shorter than Kmer length will not be found. Kmer length must be at least 1.
default:27
processing.check_reverse_complements
label:Look for reverse complements of kmers in addition to forward kmers [rcomp=t]
type:basic:boolean
default:True
processing.mask_middle_base
label:Treat the middle base of a kmer as a wildcard to increase sensitivity in the presence of errors [maskmiddle=t]
type:basic:boolean
default:True
processing.min_kmer_hits
label:Minimum number of kmer hits [minkmerhits=1]
type:basic:integer
description:Reads need at least this many matching kmers to be considered matching the reference.
default:1
processing.min_kmer_fraction
label:Minimum kmer fraction [minkmerfraction=0.0]
type:basic:decimal
description:A read needs at least this fraction of its total kmers to hit a reference in order to be considered a match. If this and ‘Minimum number of kmer hits’ are set, the greater is used.
default:0.0
processing.min_coverage_fraction
label:Minimum coverage fraction [mincovfraction=0.0]
type:basic:decimal
description:A read needs at least this fraction of its total bases to be covered by reference kmers to be considered a match. If specified, ‘Minimum coverage fraction’ overrides ‘Minimum number of kmer hits’ and ‘Minimum kmer fraction’.
default:0.0
processing.hamming_distance
label:Maximum Hamming distance for kmers (substitutions only) [hammingdistance=0]
type:basic:integer
default:0
processing.query_hamming_distance
label:Hamming distance for query kmers [qhdist=0]
type:basic:integer
default:0
processing.edit_distance
label:Maximum edit distance from reference kmers (substitutions and indels) [editdistance=0]
type:basic:integer
default:0
processing.hamming_distance2
label:Hamming distance for short kmers when looking for shorter kmers [hammingdistance2=0]
type:basic:integer
default:0
processing.query_hamming_distance2
label:Hamming distance for short query kmers when looking for shorter kmers [qhdist2=0]
type:basic:integer
default:0
processing.edit_distance2
label:Maximum edit distance from short reference kmers (substitutions and indels) when looking for shorter kmers [editdistance2=0]
type:basic:integer
default:0
processing.forbid_N
label:Forbid matching of read kmers containing N [forbidn=f]
type:basic:boolean
description:By default, these will match a reference ‘A’ if ‘Maximum Hamming distance for kmers’ > 0 or ‘Maximum edit distance from reference kmers’ > 0, to increase sensitivity.
default:False
processing.find_best_match
label:If multiple matches, associate read with sequence sharing most kmers [findbestmatch=f]
type:basic:boolean
default:True
operations.k_trim
label:Trimming protocol to remove bases matching reference kmers from reads [ktrim=f]
type:basic:string
default:f
choices:
  • Don’t trim: f
  • Trim to the right: r
  • Trim to the left: l
operations.k_mask
label:Symbol to replace bases matching reference kmers [kmask=f]
type:basic:string
description:Allows any non-whitespace character other than t or f. Processes short kmers on both ends.
default:f
operations.mask_fully_covered
label:Only mask bases that are fully covered by kmers [maskfullycovered=f]
type:basic:boolean
default:False
operations.min_k
label:Look for shorter kmers at read tips down to this length when k-trimming or masking [mink=0]
type:basic:integer
description:-1 means disabled. Enabling this will disable treating the middle base of a kmer as a wildcard to increase sensitivity in the presence of errors.
default:-1
operations.quality_trim
label:Trimming protocol to remove bases with quality below the minimum average region quality from read ends [qtrim=f]
type:basic:string
description:Performed after looking for kmers. If enabled, set also ‘Average quality below which to trim region’.
default:f
choices:
  • Trim neither end: f
  • Trim both ends: rl
  • Trim only right end: r
  • Trim only left end: l
  • Use sliding window: w
operations.trim_quality
label:Average quality below which to trim region [trimq=6]
type:basic:integer
description:Set trimming protocol to enable this parameter.
disabled:operations.quality_trim == ‘f’
default:6
operations.trim_poly_A
label:Minimum length of poly-A or poly-T tails to trim on either end of reads [trimpolya=0]
type:basic:integer
default:0
operations.min_length_fraction
label:Minimum length fraction [mlf=0]
type:basic:decimal
description:Reads shorter than this fraction of original length after trimming will be discarded.
default:0.0
operations.max_length
label:Maximum length [maxlength]
type:basic:integer
description:Reads longer than this after trimming will be discarded.
required:False
operations.min_average_quality
label:Minimum average quality [minavgquality=0]
type:basic:integer
description:Reads with average quality (after trimming) below this will be discarded.
default:0
operations.min_average_quality_bases
label:Number of initial bases to calculate minimum average quality from [maqb=0]
type:basic:integer
description:Used only if positive.
default:0
operations.min_base_quality
label:Minimum base quality below which reads are discarded after trimming [minbasequality=0]
type:basic:integer
default:0
operations.min_consecutive_bases
label:Minimum number of consecutive called bases [mcb=0]
type:basic:integer
default:0
operations.trim_pad
label:Number of bases to trim around matching kmers [tp=0]
type:basic:integer
default:0
operations.min_overlap
label:Minimum number of overlapping bases [minoverlap=14]
type:basic:integer
description:Require this many bases of overlap for detection.
default:14
operations.min_insert
label:Minimum insert size [mininsert=40]
type:basic:integer
description:Require insert size of at least this for overlap. Should be reduced to 16 for small RNA sequencing.
default:40
operations.force_trim_left
label:Position from which to trim bases to the left [forcetrimleft=0]
type:basic:integer
default:0
operations.force_trim_right
label:Position from which to trim bases to the right [forcetrimright=0]
type:basic:integer
default:0
operations.force_trim_right2
label:Number of bases to trim from the right end [forcetrimright2=0]
type:basic:integer
default:0
operations.force_trim_mod
label:Modulo to right-trim reads [forcetrimmod=0]
type:basic:integer
description:Trim reads to the largest multiple of modulo.
default:0
operations.restrict_left
label:Number of leftmost bases to look in for kmer matches [restrictleft=0]
type:basic:integer
default:0
operations.restrict_right
label:Number of rightmosot bases to look in for kmer matches [restricright=0]
type:basic:integer
default:0
operations.min_GC
label:Minimum GC content [mingc=0.0]
type:basic:decimal
description:Discard reads with lower GC content.
default:0.0
operations.max_GC
label:Maximum GC content [maxgc=1.0]
type:basic:decimal
description:Discard reads with higher GC content.
default:1.0
operations.maxns
label:Max Ns after trimming [maxns=-1]
type:basic:integer
description:If non-negative, reads with more Ns than this (after trimming) will be discarded.
default:-1
operations.toss_junk
label:Discard reads with invalid characters as bases [tossjunk=f]
type:basic:boolean
default:False
header_parsing.chastity_filter
label:Discard reads that fail Illumina chastity filtering [chastityfilter=f]
type:basic:boolean
description:Discard reads with id containing ‘ 1:Y:’ or ‘ 2:Y:’.
default:False
header_parsing.barcode_filter
label:Remove reads with unexpected barcodes if barcodes are set, or barcodes containing ‘N’ otherwise [barcodefilter=f]
type:basic:boolean
description:A barcode must be the last part of the read header.
default:False
header_parsing.barcode_files
label:Barcode sequences [barcodes]
type:list:data:seq:nucleotide
required:False
header_parsing.barcode_sequences
label:Literal barcode sequences [barcodes]
type:list:basic:string
description:Literal barcode sequences can be specified by inputting them one by one and pressing Enter after each sequence.
required:False
default:[]
header_parsing.x_min
label:Minimum X coordinate [xmin=-1]
type:basic:integer
description:If positive, discard reads with a smaller X coordinate.
default:-1
header_parsing.y_min
label:Minimum Y coordinate [ymin=-1]
type:basic:integer
description:If positive, discard reads with a smaller Y coordinate.
default:-1
header_parsing.x_max
label:Maximum X coordinate [xmax=-1]
type:basic:integer
description:If positive, discard reads with a larger X coordinate.
default:-1
header_parsing.y_max
label:Maximum Y coordinate [ymax=-1]
type:basic:integer
description:If positive, discard reads with a larger Y coordinate.
default:-1
complexity.entropy
label:Minimum entropy [entropy=-1]
type:basic:decimal
description:Set between 0 and 1 to filter reads with entropy below that value. Higher is more stringent.
default:-1.0
complexity.entropy_window
label:Length of sliding window used to calculate entropy [entropywindow=50]
type:basic:integer
description:To use the sliding window set minimum entropy in range between 0.0 and 1.0.
default:50
complexity.entropy_k
label:Length of kmers used to calcuate entropy [entropyk=5]
type:basic:integer
default:5
complexity.entropy_mask
label:Mask low-entropy parts of sequences with N instead of discarding [entropymask=f]
type:basic:boolean
default:False
complexity.min_base_frequency
label:Minimum base frequency [minbasefrequency=0]
type:basic:integer
default:0
fastqc.nogroup
label:Disable grouping of bases for reads >50bp [nogroup]
type:basic:boolean
description:All reports will show data for every base in the read. Using this option will cause fastqc to crash and burn if you use it on really long reads.
default:False

Output results

fastq
label:Remaining reads
type:list:basic:file
statistics
label:Statistics
type:list:basic:file
fastqc_url
label:Quality control with FastQC
type:list:basic:file:html
fastqc_archive
label:Download FastQC archive
type:list:basic:file
BBDuk - STAR - FeatureCounts (3’ mRNA-Seq, paired-end)
data:workflow:quant:featurecounts:pairedworkflow-bbduk-star-fc-quant-paired (data:reads:fastq:paired  reads, data:genomeindex:star  star_index, list:data:seq:nucleotide  adapters, data:annotation  annotation, basic:string  stranded, basic:integer  n_reads, basic:integer  seed, basic:decimal  fraction, basic:boolean  two_pass, data:genomeindex:star  rrna_reference, data:genomeindex:star  globin_reference)[Source: v1.1.0]

This 3’ mRNA-Seq pipeline is comprised of QC, preprocessing, alignment and quantification steps. Reads are preprocessed by __BBDuk__ which removes adapters, trims reads for quality from the 3’-end, and discards reads that are too short after trimming. Preprocessed reads are aligned by __STAR__ aligner. For read-count quantification, the __FeatureCounts__ tool is used. QC steps include downsampling, QoRTs QC analysis and alignment of input reads to the rRNA/globin reference sequences. The reported alignment rate is used to asses the rRNA/globin sequence depletion rate.

Input arguments

reads
label:Paired-end reads
type:data:reads:fastq:paired
star_index
label:Star index
type:data:genomeindex:star
description:Genome index prepared by STAR aligner indexing tool.
adapters
label:Adapters
type:list:data:seq:nucleotide
description:Provide a list of sequencing adapters files (.fasta) to be removed by BBDuk.
required:False
annotation
label:Annotation
type:data:annotation
stranded
label:Select the type of kit used for library preparation.
type:basic:string
choices:
  • Strand-specific forward: forward
  • Strand-specific reverse: reverse
downsampling.n_reads
label:Number of reads
type:basic:integer
default:1000000
downsampling.advanced.seed
label:Seed
type:basic:integer
default:11
downsampling.advanced.fraction
label:Fraction
type:basic:decimal
description:Use the fraction of reads in range [0.0, 1.0] from the orignal input file instead of the absolute number of reads. If set, this will override the “Number of reads” input parameter.
required:False
downsampling.advanced.two_pass
label:2-pass mode
type:basic:boolean
description:Enable two-pass mode when down-sampling. Two-pass mode is twice as slow but with much reduced memory.
default:False
qc.rrna_reference
label:Indexed rRNA reference sequence
type:data:genomeindex:star
description:Reference sequence index prepared by STAR aligner indexing tool.
qc.globin_reference
label:Indexed Globin reference sequence
type:data:genomeindex:star
description:Reference sequence index prepared by STAR aligner indexing tool.

Output results

BBDuk - STAR - FeatureCounts (3’ mRNA-Seq, single-end)
data:workflow:quant:featurecounts:singleworkflow-bbduk-star-fc-quant-single (data:reads:fastq:single  reads, data:genomeindex:star  star_index, list:data:seq:nucleotide  adapters, data:annotation  annotation, basic:string  stranded, basic:integer  n_reads, basic:integer  seed, basic:decimal  fraction, basic:boolean  two_pass, data:genomeindex:star  rrna_reference, data:genomeindex:star  globin_reference)[Source: v1.1.0]

This 3’ mRNA-Seq pipeline is comprised of QC, preprocessing, alignment and quantification steps. Reads are preprocessed by __BBDuk__ which removes adapters, trims reads for quality from the 3’-end, and discards reads that are too short after trimming. Preprocessed reads are aligned by __STAR__ aligner. For read-count quantification, the __FeatureCounts__ tool is used. QC steps include downsampling, QoRTs QC analysis and alignment of input reads to the rRNA/globin reference sequences. The reported alignment rate is used to asses the rRNA/globin sequence depletion rate.

Input arguments

reads
label:Input single-end reads
type:data:reads:fastq:single
star_index
label:Star index
type:data:genomeindex:star
description:Genome index prepared by STAR aligner indexing tool.
adapters
label:Adapters
type:list:data:seq:nucleotide
description:Provide a list of sequencing adapters files (.fasta) to be removed by BBDuk.
required:False
annotation
label:Annotation
type:data:annotation
stranded
label:Select the type of kit used for library preparation.
type:basic:string
choices:
  • Strand-specific forward: forward
  • Strand-specific reverse: reverse
downsampling.n_reads
label:Number of reads
type:basic:integer
default:1000000
downsampling.advanced.seed
label:Seed
type:basic:integer
default:11
downsampling.advanced.fraction
label:Fraction
type:basic:decimal
description:Use the fraction of reads in range [0.0, 1.0] from the orignal input file instead of the absolute number of reads. If set, this will override the “Number of reads” input parameter.
required:False
downsampling.advanced.two_pass
label:2-pass mode
type:basic:boolean
description:Enable two-pass mode when down-sampling. Two-pass mode is twice as slow but with much reduced memory.
default:False
qc.rrna_reference
label:Indexed rRNA reference sequence
type:data:genomeindex:star
description:Reference sequence index prepared by STAR aligner indexing tool.
qc.globin_reference
label:Indexed Globin reference sequence
type:data:genomeindex:star
description:Reference sequence index prepared by STAR aligner indexing tool.

Output results

BBDuk - STAR - HTSeq-count (paired-end)
data:workflow:rnaseq:htseq:pairedworkflow-bbduk-star-htseq-paired (data:reads:fastq:paired  reads, data:genomeindex:star  star_index, list:data:seq:nucleotide  adapters, data:annotation  annotation, basic:string  stranded)[Source: v1.0.1]

This RNA-seq pipeline is comprised of three steps, preprocessing, alignment, and quantification. First, reads are preprocessed by __BBDuk__ which removes adapters, trims reads for quality from the 3’-end, and discards reads that are too short after trimming. Compared to similar tools, BBDuk is regarded for its computational efficiency. Next, preprocessed reads are aligned by __STAR__ aligner. At the time of implementation, STAR is considered a state-of-the-art tool that consistently produces accurate results from diverse sets of reads, and performs well even with default settings. For more information see [this comparison of RNA-seq aligners](https://www.nature.com/articles/nmeth.4106). Finally, aligned reads are summarized to genes by __HTSeq-count__. Compared to featureCounts, HTSeq-count is not as computationally efficient. All three tools in this workflow support parallelization to accelerate the analysis.

Input arguments

reads
label:Paired-end reads
type:data:reads:fastq:paired
star_index
label:Star index
type:data:genomeindex:star
description:Genome index prepared by STAR aligner indexing tool.
adapters
label:Adapters
type:list:data:seq:nucleotide
description:Provide a list of sequencing adapters files (.fasta) to be removed by BBDuk.
required:False
annotation
label:Annotation
type:data:annotation
stranded
label:Select the QuantSeq kit used for library preparation.
type:basic:string
choices:
  • QuantSeq FWD: yes
  • QuantSeq REV: reverse

Output results

BBDuk - STAR - HTSeq-count (single-end)
data:workflow:rnaseq:htseq:singleworkflow-bbduk-star-htseq (data:reads:fastq:single  reads, data:genomeindex:star  star_index, list:data:seq:nucleotide  adapters, data:annotation  annotation, basic:string  stranded)[Source: v1.0.1]

This RNA-seq pipeline is comprised of three steps, preprocessing, alignment, and quantification. First, reads are preprocessed by __BBDuk__ which removes adapters, trims reads for quality from the 3’-end, and discards reads that are too short after trimming. Compared to similar tools, BBDuk is regarded for its computational efficiency. Next, preprocessed reads are aligned by __STAR__ aligner. At the time of implementation, STAR is considered a state-of-the-art tool that consistently produces accurate results from diverse sets of reads, and performs well even with default settings. For more information see [this comparison of RNA-seq aligners](https://www.nature.com/articles/nmeth.4106). Finally, aligned reads are summarized to genes by __HTSeq-count__. Compared to featureCounts, HTSeq-count is not as computationally efficient. All three tools in this workflow support parallelization to accelerate the analysis.

Input arguments

reads
label:Input single-end reads
type:data:reads:fastq:single
star_index
label:Star index
type:data:genomeindex:star
description:Genome index prepared by STAR aligner indexing tool.
adapters
label:Adapters
type:list:data:seq:nucleotide
description:Provide a list of sequencing adapters files (.fasta) to be removed by BBDuk.
required:False
annotation
label:annotation
type:data:annotation
stranded
label:Select the QuantSeq kit used for library preparation.
type:basic:string
choices:
  • QuantSeq FWD: yes
  • QuantSeq REV: reverse

Output results

BBDuk - STAR - featureCounts - QC (paired-end)
data:workflow:rnaseq:featurecounts:qcworkflow-bbduk-star-featurecounts-qc-paired (data:reads:fastq:paired  reads, list:data:seq:nucleotide  adapters, basic:boolean  show_advanced, list:basic:string  custom_adapter_sequences, basic:integer  kmer_length, basic:integer  min_k, basic:integer  hamming_distance, basic:integer  maxns, basic:integer  trim_quality, basic:integer  min_length, data:genomeindex:star  genome, basic:boolean  show_advanced, basic:boolean  unstranded, basic:boolean  noncannonical, basic:boolean  chimeric, basic:integer  chimSegmentMin, basic:boolean  quantmode, basic:boolean  singleend, basic:boolean  gene_counts, basic:string  outFilterType, basic:integer  outFilterMultimapNmax, basic:integer  outFilterMismatchNmax, basic:decimal  outFilterMismatchNoverLmax, basic:integer  outFilterScoreMin, basic:integer  alignSJoverhangMin, basic:integer  alignSJDBoverhangMin, basic:integer  alignIntronMin, basic:integer  alignIntronMax, basic:integer  alignMatesGapMax, basic:string  alignEndsType, basic:string  outSAMunmapped, basic:string  outSAMattributes, basic:string  outSAMattrRGline, data:annotation  annotation, basic:boolean  show_advanced, basic:string  assay_type, data:index:salmon  cdna_index, basic:integer  n_reads, basic:string  feature_class, basic:string  feature_type, basic:string  id_attribute, basic:integer  n_reads, basic:integer  seed, basic:decimal  fraction, basic:boolean  two_pass, data:genomeindex:star  rrna_reference, data:genomeindex:star  globin_reference)[Source: v1.4.0]

This RNA-seq pipeline is comprised of three steps preprocessing, alignment, and quantification. First, reads are preprocessed by __BBDuk__ which removes adapters, trims reads for quality from the 3’-end, and discards reads that are too short after trimming. Compared to similar tools, BBDuk is regarded for its computational efficiency. Next, preprocessed reads are aligned by __STAR__ aligner. At the time of implementation, STAR is considered a state-of-the-art tool that consistently produces accurate results from diverse sets of reads, and performs well even with default settings. For more information see [this comparison of RNA-seq aligners](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5792058/). Finally, aligned reads are summarized to genes by __featureCounts__. Gaining wide adoption among the bioinformatics community, featureCounts yields expressions in a computationally efficient manner. All three tools in this workflow support parallelization to accelerate the analysis. rRNA contamination rate in the sample is determined using the STAR aligner. Quality-trimmed reads are down-sampled (using Seqtk tool) and aligned to the rRNA reference sequences. The alignment rate indicates the percentage of the reads in the sample that are derived from the rRNA sequences.

Input arguments

preprocessing.reads
label:Reads
type:data:reads:fastq:paired
preprocessing.adapters
label:Adapters
type:list:data:seq:nucleotide
required:False
preprocessing.show_advanced
label:Show advanced parameters
type:basic:boolean
default:False
preprocessing.custom_adapter_sequences
label:Custom adapter sequences [literal]
type:list:basic:string
description:Custom adapter sequences can be specified by inputting them one by one and pressing Enter after each sequence.
required:False
hidden:!preprocessing.show_advanced
default:[]
preprocessing.kmer_length
label:K-mer length
type:basic:integer
description:K-mer length must be smaller or equal to the length of adapters.
hidden:!preprocessing.show_advanced
default:23
preprocessing.min_k
label:Minimum k-mer length at right end of reads used for trimming
type:basic:integer
disabled:preprocessing.adapters.length === 0 && preprocessing.custom_adapter_sequences.length === 0
hidden:!preprocessing.show_advanced
default:11
preprocessing.hamming_distance
label:Maximum Hamming distance for k-mers
type:basic:integer
hidden:!preprocessing.show_advanced
default:1
preprocessing.maxns
label:Max Ns after trimming [maxns=-1]
type:basic:integer
description:If non-negative, reads with more Ns than this (after trimming) will be discarded.
hidden:!preprocessing.show_advanced
default:-1
preprocessing.trim_quality
label:Quality below which to trim reads from the right end
type:basic:integer
description:Phred algorithm is used, which is more accurate than naive trimming.
hidden:!preprocessing.show_advanced
default:10
preprocessing.min_length
label:Minimum read length
type:basic:integer
description:Reads shorter than minimum read length after trimming are discarded.
hidden:!preprocessing.show_advanced
default:20
alignment.genome
label:Indexed reference genome
type:data:genomeindex:star
description:Genome index prepared by STAR aligner indexing tool.
alignment.show_advanced
label:Show advanced parameters
type:basic:boolean
default:False
alignment.unstranded
label:The data is unstranded
type:basic:boolean
description:For unstranded RNA-seq data, Cufflinks/Cuffdiff require spliced alignments with XS strand attribute, which STAR will generate with –outSAMstrandField intronMotif option. As required, the XS strand attribute will be generated for all alignments that contain splice junctions. The spliced alignments that have undefined strand (i.e. containing only non-canonical unannotated junctions) will be suppressed. If you have stranded RNA-seq data, you do not need to use any specific STAR options. Instead, you need to run Cufflinks with the library option –library-type options. For example, c ufflinks –library-type fr-firststrand should be used for the standard dUTP protocol, including Illumina’s stranded Tru-Seq. This option has to be used only for Cufflinks runs and not for STAR runs.
hidden:!alignment.show_advanced
default:False
alignment.noncannonical
label:Remove non-cannonical junctions (Cufflinks compatibility)
type:basic:boolean
description:It is recommended to remove the non-canonical junctions for Cufflinks runs using –outFilterIntronMotifs RemoveNoncanonical.
hidden:!alignment.show_advanced
default:False
alignment.detect_chimeric.chimeric
label:Detect chimeric and circular alignments
type:basic:boolean
description:To switch on detection of chimeric (fusion) alignments (in addition to normal mapping), –chimSegmentMin should be set to a positive value. Each chimeric alignment consists of two “segments”. Each segment is non-chimeric on its own, but the segments are chimeric to each other (i.e. the segments belong to different chromosomes, or different strands, or are far from each other). Both segments may contain splice junctions, and one of the segments may contain portions of both mates. –chimSegmentMin parameter controls the minimum mapped length of the two segments that is allowed. For example, if you have 2x75 reads and used –chimSegmentMin 20, a chimeric alignment with 130b on one chromosome and 20b on the other will be output, while 135 + 15 won’t be.
default:False
alignment.detect_chimeric.chimSegmentMin
label:–chimSegmentMin
type:basic:integer
disabled:detect_chimeric.chimeric != true
default:20
alignment.t_coordinates.quantmode
label:Output in transcript coordinates
type:basic:boolean
description:With –quantMode TranscriptomeSAM option STAR will output alignments translated into transcript coordinates in the Aligned.toTranscriptome.out.bam file (in addition to alignments in genomic coordinates in Aligned.*.sam/bam files). These transcriptomic alignments can be used with various transcript quantification software that require reads to be mapped to transcriptome, such as RSEM or eXpress.
default:False
alignment.t_coordinates.singleend
label:Allow soft-clipping and indels
type:basic:boolean
description:By default, the output satisfies RSEM requirements: soft-clipping or indels are not allowed. Use –quantTranscriptomeBan Singleend to allow insertions, deletions ans soft-clips in the transcriptomic alignments, which can be used by some expression quantification software (e.g. eXpress).
disabled:t_coordinates.quantmode != true
default:False
alignment.t_coordinates.gene_counts
label:Count reads
type:basic:boolean
description:With –quantMode GeneCounts option STAR will count number reads per gene while mapping. A read is counted if it overlaps (1nt or more) one and only one gene. Both ends of the paired-end read are checked for overlaps. The counts coincide with those produced by htseq-count with default parameters. ReadsPerGene.out.tab file with 4 columns which correspond to different strandedness options: column 1: gene ID; column 2: counts for unstranded RNA-seq; column 3: counts for the 1st read strand aligned with RNA (htseq-count option -s yes); column 4: counts for the 2nd read strand aligned with RNA (htseq-count option -s reverse).
disabled:t_coordinates.quantmode != true
default:False
alignment.filtering.outFilterType
label:Type of filtering
type:basic:string
description:Normal: standard filtering using only current alignment; BySJout: keep only those reads that contain junctions that passed filtering into SJ.out.tab
default:Normal
choices:
  • Normal: Normal
  • BySJout: BySJout
alignment.filtering.outFilterMultimapNmax
label:–outFilterMultimapNmax
type:basic:integer
description:Read alignments will be output only if the read maps fewer than this value, otherwise no alignments will be output (default: 10).
required:False
alignment.filtering.outFilterMismatchNmax
label:–outFilterMismatchNmax
type:basic:integer
description:Alignment will be output only if it has fewer mismatches than this value (default: 10).
required:False
alignment.filtering.outFilterMismatchNoverLmax
label:–outFilterMismatchNoverLmax
type:basic:decimal
description:Max number of mismatches per pair relative to read length: for 2x100b, max number of mismatches is 0.06*200=8 for the paired read.
required:False
alignment.filtering.outFilterScoreMin
label:–outFilterScoreMin
type:basic:integer
description:Alignment will be output only if its score is higher than or equal to this value (default: 0).
required:False
alignment.alignment.alignSJoverhangMin
label:–alignSJoverhangMin
type:basic:integer
description:Minimum overhang (i.e. block size) for spliced alignments (default: 5).
required:False
alignment.alignment.alignSJDBoverhangMin
label:–alignSJDBoverhangMin
type:basic:integer
description:Minimum overhang (i.e. block size) for annotated (sjdb) spliced alignments (default: 3).
required:False
alignment.alignment.alignIntronMin
label:–alignIntronMin
type:basic:integer
description:Minimum intron size: genomic gap is considered intron if its length >= alignIntronMin, otherwise it is considered Deletion (default: 21).
required:False
alignment.alignment.alignIntronMax
label:–alignIntronMax
type:basic:integer
description:Maximum intron size, if 0, max intron size will be determined by (2pow(winBinNbits)*winAnchorDistNbins) (default: 0).
required:False
alignment.alignment.alignMatesGapMax
label:–alignMatesGapMax
type:basic:integer
description:Maximum gap between two mates, if 0, max intron gap will be determined by (2pow(winBinNbits)*winAnchorDistNbins) (default: 0).
required:False
alignment.alignment.alignEndsType
label:–alignEndsType
type:basic:string
description:Type of read ends alignment (default: Local).
required:False
default:Local
choices:
  • Local: Local
  • EndToEnd: EndToEnd
  • Extend5pOfRead1: Extend5pOfRead1
  • Extend5pOfReads12: Extend5pOfReads12
alignment.output_sam_bam.outSAMunmapped
label:–outSAMunmapped
type:basic:string
description:Output of unmapped reads in the SAM format.
required:False
default:None
choices:
  • None: None
  • Within: Within
alignment.output_sam_bam.outSAMattributes
label:–outSAMattributes
type:basic:string
description:a string of desired SAM attributes, in the order desired for the output SAM.
required:False
default:Standard
choices:
  • None: None
  • Standard: Standard
  • All: All
alignment.output_sam_bam.outSAMattrRGline
label:–outSAMattrRGline
type:basic:string
description:SAM/BAM read group line. The first word contains the read group identifier and must start with “ID:”, e.g. –outSAMattrRGline ID:xxx CN:yy “DS:z z z”
required:False
quantification.annotation
label:Annotation
type:data:annotation
quantification.show_advanced
label:Show advanced parameters
type:basic:boolean
default:False
quantification.assay_type
label:Assay type
type:basic:string
description:In strand non-specific assay a read is considered overlapping with a feature regardless of whether it is mapped to the same or the opposite strand as the feature. In strand-specific forward assay and single reads, the read has to be mapped to the same strand as the feature. For paired-end reads, the first read has to be on the same strand and the second read on the opposite strand. In strand-specific reverse assay these rules are reversed.
hidden:!quantification.show_advanced
default:non_specific
choices:
  • Strand non-specific: non_specific
  • Strand-specific forward: forward
  • Strand-specific reverse: reverse
  • Detect automatically: auto
quantification.cdna_index
label:cDNA index file
type:data:index:salmon
description:Transcriptome index file created using the Salmon indexing tool. cDNA (transcriptome) sequences used for index file creation must be derived from the same species as the input sequencing reads to obtain the reliable analysis results.
required:False
hidden:quantification.assay_type != ‘auto’
quantification.n_reads
label:Number of reads in subsampled alignment file
type:basic:integer
description:Alignment (.bam) file subsample size. Increase the number of reads to make automatic detection more reliable. Decrease the number of reads to make automatic detection run faster.
hidden:quantification.assay_type != ‘auto’
default:5000000
quantification.feature_class
label:Feature class
type:basic:string
description:Feature class (3rd column in GTF/GFF3 file) to be used. All other features will be ignored.
hidden:!quantification.show_advanced
default:exon
quantification.feature_type
label:Feature type
type:basic:string
description:The type of feature the quantification program summarizes over (e.g. gene or transcript-level analysis). The value of this parameter needs to be chosen in line with ‘ID attribute’ below.
hidden:!quantification.show_advanced
default:gene
choices:
  • gene: gene
  • transcript: transcript
quantification.id_attribute
label:ID attribute
type:basic:string
description:GTF/GFF3 attribute to be used as feature ID. Several GTF/GFF3 lines with the same feature ID are considered as parts of the same feature. The feature ID is used to identify the counts in the output table. In GTF files this is usually ‘gene_id’, in GFF3 files this is often ‘ID’, and ‘transcript_id’ is frequently a valid choice for both annotation formats.
hidden:!quantification.show_advanced
default:gene_id
choices:
  • gene_id: gene_id
  • transcript_id: transcript_id
  • ID: ID
  • geneid: geneid
downsampling.n_reads
label:Number of reads
type:basic:integer
default:1000000
downsampling.advanced.seed
label:Seed
type:basic:integer
default:11
downsampling.advanced.fraction
label:Fraction
type:basic:decimal
description:Use the fraction of reads [0 - 1.0] from the orignal input file instead of the absolute number of reads. If set, this will override the “Number of reads” input parameter.
required:False
downsampling.advanced.two_pass
label:2-pass mode
type:basic:boolean
description:Enable two-pass mode when down-sampling. Two-pass mode is twice as slow but with much reduced memory.
default:False
qc.rrna_reference
label:Indexed rRNA reference sequence
type:data:genomeindex:star
description:Reference sequence index prepared by STAR aligner indexing tool.
qc.globin_reference
label:Indexed Globin reference sequence
type:data:genomeindex:star
description:Reference sequence index prepared by STAR aligner indexing tool.

Output results

BBDuk - STAR - featureCounts - QC (single-end)
data:workflow:rnaseq:featurecounts:qcworkflow-bbduk-star-featurecounts-qc-single (data:reads:fastq:single  reads, list:data:seq:nucleotide  adapters, basic:boolean  show_advanced, list:basic:string  custom_adapter_sequences, basic:integer  kmer_length, basic:integer  min_k, basic:integer  hamming_distance, basic:integer  maxns, basic:integer  trim_quality, basic:integer  min_length, data:genomeindex:star  genome, basic:boolean  show_advanced, basic:boolean  unstranded, basic:boolean  noncannonical, basic:boolean  chimeric, basic:integer  chimSegmentMin, basic:boolean  quantmode, basic:boolean  singleend, basic:boolean  gene_counts, basic:string  outFilterType, basic:integer  outFilterMultimapNmax, basic:integer  outFilterMismatchNmax, basic:decimal  outFilterMismatchNoverLmax, basic:integer  outFilterScoreMin, basic:integer  alignSJoverhangMin, basic:integer  alignSJDBoverhangMin, basic:integer  alignIntronMin, basic:integer  alignIntronMax, basic:integer  alignMatesGapMax, basic:string  alignEndsType, basic:string  outSAMunmapped, basic:string  outSAMattributes, basic:string  outSAMattrRGline, data:annotation  annotation, basic:boolean  show_advanced, basic:string  assay_type, data:index:salmon  cdna_index, basic:integer  n_reads, basic:string  feature_class, basic:string  feature_type, basic:string  id_attribute, basic:integer  n_reads, basic:integer  seed, basic:decimal  fraction, basic:boolean  two_pass, data:genomeindex:star  rrna_reference, data:genomeindex:star  globin_reference)[Source: v1.4.0]

This RNA-seq pipeline is comprised of three steps preprocessing, alignment, and quantification. First, reads are preprocessed by __BBDuk__ which removes adapters, trims reads for quality from the 3’-end, and discards reads that are too short after trimming. Compared to similar tools, BBDuk is regarded for its computational efficiency. Next, preprocessed reads are aligned by __STAR__ aligner. At the time of implementation, STAR is considered a state-of-the-art tool that consistently produces accurate results from diverse sets of reads, and performs well even with default settings. For more information see [this comparison of RNA-seq aligners](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5792058/). Finally, aligned reads are summarized to genes by __featureCounts__. Gaining wide adoption among the bioinformatics community, featureCounts yields expressions in a computationally efficient manner. All three tools in this workflow support parallelization to accelerate the analysis. rRNA contamination rate in the sample is determined using the STAR aligner. Quality-trimmed reads are down-sampled (using Seqtk tool) and aligned to the rRNA reference sequences. The alignment rate indicates the percentage of the reads in the sample that are derived from the rRNA sequences.

Input arguments

preprocessing.reads
label:Reads
type:data:reads:fastq:single
preprocessing.adapters
label:Adapters
type:list:data:seq:nucleotide
required:False
preprocessing.show_advanced
label:Show advanced parameters
type:basic:boolean
default:False
preprocessing.custom_adapter_sequences
label:Custom adapter sequences [literal]
type:list:basic:string
description:Custom adapter sequences can be specified by inputting them one by one and pressing Enter after each sequence.
required:False
hidden:!preprocessing.show_advanced
default:[]
preprocessing.kmer_length
label:K-mer length
type:basic:integer
description:K-mer length must be smaller or equal to the length of adapters.
hidden:!preprocessing.show_advanced
default:23
preprocessing.min_k
label:Minimum k-mer length at right end of reads used for trimming
type:basic:integer
disabled:preprocessing.adapters.length === 0 && preprocessing.custom_adapter_sequences.length === 0
hidden:!preprocessing.show_advanced
default:11
preprocessing.hamming_distance
label:Maximum Hamming distance for k-mers
type:basic:integer
hidden:!preprocessing.show_advanced
default:1
preprocessing.maxns
label:Max Ns after trimming [maxns=-1]
type:basic:integer
description:If non-negative, reads with more Ns than this (after trimming) will be discarded.
hidden:!preprocessing.show_advanced
default:-1
preprocessing.trim_quality
label:Quality below which to trim reads from the right end
type:basic:integer
description:Phred algorithm is used, which is more accurate than naive trimming.
hidden:!preprocessing.show_advanced
default:10
preprocessing.min_length
label:Minimum read length
type:basic:integer
description:Reads shorter than minimum read length after trimming are discarded.
hidden:!preprocessing.show_advanced
default:20
alignment.genome
label:Indexed reference genome
type:data:genomeindex:star
description:Genome index prepared by STAR aligner indexing tool.
alignment.show_advanced
label:Show advanced parameters
type:basic:boolean
default:False
alignment.unstranded
label:The data is unstranded
type:basic:boolean
description:For unstranded RNA-seq data, Cufflinks/Cuffdiff require spliced alignments with XS strand attribute, which STAR will generate with –outSAMstrandField intronMotif option. As required, the XS strand attribute will be generated for all alignments that contain splice junctions. The spliced alignments that have undefined strand (i.e. containing only non-canonical unannotated junctions) will be suppressed. If you have stranded RNA-seq data, you do not need to use any specific STAR options. Instead, you need to run Cufflinks with the library option –library-type options. For example, c ufflinks –library-type fr-firststrand should be used for the standard dUTP protocol, including Illumina’s stranded Tru-Seq. This option has to be used only for Cufflinks runs and not for STAR runs.
hidden:!alignment.show_advanced
default:False
alignment.noncannonical
label:Remove non-cannonical junctions (Cufflinks compatibility)
type:basic:boolean
description:It is recommended to remove the non-canonical junctions for Cufflinks runs using –outFilterIntronMotifs RemoveNoncanonical.
hidden:!alignment.show_advanced
default:False
alignment.detect_chimeric.chimeric
label:Detect chimeric and circular alignments
type:basic:boolean
description:To switch on detection of chimeric (fusion) alignments (in addition to normal mapping), –chimSegmentMin should be set to a positive value. Each chimeric alignment consists of two “segments”. Each segment is non-chimeric on its own, but the segments are chimeric to each other (i.e. the segments belong to different chromosomes, or different strands, or are far from each other). Both segments may contain splice junctions, and one of the segments may contain portions of both mates. –chimSegmentMin parameter controls the minimum mapped length of the two segments that is allowed. For example, if you have 2x75 reads and used –chimSegmentMin 20, a chimeric alignment with 130b on one chromosome and 20b on the other will be output, while 135 + 15 won’t be.
default:False
alignment.detect_chimeric.chimSegmentMin
label:–chimSegmentMin
type:basic:integer
disabled:detect_chimeric.chimeric != true
default:20
alignment.t_coordinates.quantmode
label:Output in transcript coordinates
type:basic:boolean
description:With –quantMode TranscriptomeSAM option STAR will output alignments translated into transcript coordinates in the Aligned.toTranscriptome.out.bam file (in addition to alignments in genomic coordinates in Aligned.*.sam/bam files). These transcriptomic alignments can be used with various transcript quantification software that require reads to be mapped to transcriptome, such as RSEM or eXpress.
default:False
alignment.t_coordinates.singleend
label:Allow soft-clipping and indels
type:basic:boolean
description:By default, the output satisfies RSEM requirements: soft-clipping or indels are not allowed. Use –quantTranscriptomeBan Singleend to allow insertions, deletions ans soft-clips in the transcriptomic alignments, which can be used by some expression quantification software (e.g. eXpress).
disabled:t_coordinates.quantmode != true
default:False
alignment.t_coordinates.gene_counts
label:Count reads
type:basic:boolean
description:With –quantMode GeneCounts option STAR will count number reads per gene while mapping. A read is counted if it overlaps (1nt or more) one and only one gene. Both ends of the paired-end read are checked for overlaps. The counts coincide with those produced by htseq-count with default parameters. ReadsPerGene.out.tab file with 4 columns which correspond to different strandedness options: column 1: gene ID; column 2: counts for unstranded RNA-seq; column 3: counts for the 1st read strand aligned with RNA (htseq-count option -s yes); column 4: counts for the 2nd read strand aligned with RNA (htseq-count option -s reverse).
disabled:t_coordinates.quantmode != true
default:False
alignment.filtering.outFilterType
label:Type of filtering
type:basic:string
description:Normal: standard filtering using only current alignment; BySJout: keep only those reads that contain junctions that passed filtering into SJ.out.tab
default:Normal
choices:
  • Normal: Normal
  • BySJout: BySJout
alignment.filtering.outFilterMultimapNmax
label:–outFilterMultimapNmax
type:basic:integer
description:Read alignments will be output only if the read maps fewer than this value, otherwise no alignments will be output (default: 10).
required:False
alignment.filtering.outFilterMismatchNmax
label:–outFilterMismatchNmax
type:basic:integer
description:Alignment will be output only if it has fewer mismatches than this value (default: 10).
required:False
alignment.filtering.outFilterMismatchNoverLmax
label:–outFilterMismatchNoverLmax
type:basic:decimal
description:Max number of mismatches per pair relative to read length: for 2x100b, max number of mismatches is 0.06*200=8 for the paired read.
required:False
alignment.filtering.outFilterScoreMin
label:–outFilterScoreMin
type:basic:integer
description:Alignment will be output only if its score is higher than or equal to this value (default: 0).
required:False
alignment.alignment.alignSJoverhangMin
label:–alignSJoverhangMin
type:basic:integer
description:Minimum overhang (i.e. block size) for spliced alignments (default: 5).
required:False
alignment.alignment.alignSJDBoverhangMin
label:–alignSJDBoverhangMin
type:basic:integer
description:Minimum overhang (i.e. block size) for annotated (sjdb) spliced alignments (default: 3).
required:False
alignment.alignment.alignIntronMin
label:–alignIntronMin
type:basic:integer
description:Minimum intron size: genomic gap is considered intron if its length >= alignIntronMin, otherwise it is considered Deletion (default: 21).
required:False
alignment.alignment.alignIntronMax
label:–alignIntronMax
type:basic:integer
description:Maximum intron size, if 0, max intron size will be determined by (2pow(winBinNbits)*winAnchorDistNbins) (default: 0).
required:False
alignment.alignment.alignMatesGapMax
label:–alignMatesGapMax
type:basic:integer
description:Maximum gap between two mates, if 0, max intron gap will be determined by (2pow(winBinNbits)*winAnchorDistNbins) (default: 0).
required:False
alignment.alignment.alignEndsType
label:–alignEndsType
type:basic:string
description:Type of read ends alignment (default: Local).
required:False
default:Local
choices:
  • Local: Local
  • EndToEnd: EndToEnd
  • Extend5pOfRead1: Extend5pOfRead1
  • Extend5pOfReads12: Extend5pOfReads12
alignment.output_sam_bam.outSAMunmapped
label:–outSAMunmapped
type:basic:string
description:Output of unmapped reads in the SAM format.
required:False
default:None
choices:
  • None: None
  • Within: Within
alignment.output_sam_bam.outSAMattributes
label:–outSAMattributes
type:basic:string
description:a string of desired SAM attributes, in the order desired for the output SAM.
required:False
default:Standard
choices:
  • None: None
  • Standard: Standard
  • All: All
alignment.output_sam_bam.outSAMattrRGline
label:–outSAMattrRGline
type:basic:string
description:SAM/BAM read group line. The first word contains the read group identifier and must start with “ID:”, e.g. –outSAMattrRGline ID:xxx CN:yy “DS:z z z”
required:False
quantification.annotation
label:Annotation
type:data:annotation
quantification.show_advanced
label:Show advanced parameters
type:basic:boolean
default:False
quantification.assay_type
label:Assay type
type:basic:string
description:In strand non-specific assay a read is considered overlapping with a feature regardless of whether it is mapped to the same or the opposite strand as the feature. In strand-specific forward assay and single reads, the read has to be mapped to the same strand as the feature. For paired-end reads, the first read has to be on the same strand and the second read on the opposite strand. In strand-specific reverse assay these rules are reversed.
hidden:!quantification.show_advanced
default:non_specific
choices:
  • Strand non-specific: non_specific
  • Strand-specific forward: forward
  • Strand-specific reverse: reverse
  • Detect automatically: auto
quantification.cdna_index
label:cDNA index file
type:data:index:salmon
description:Transcriptome index file created using the Salmon indexing tool. cDNA (transcriptome) sequences used for index file creation must be derived from the same species as the input sequencing reads to obtain the reliable analysis results.
required:False
hidden:quantification.assay_type != ‘auto’
quantification.n_reads
label:Number of reads in subsampled alignment file
type:basic:integer
description:Alignment (.bam) file subsample size. Increase the number of reads to make automatic detection more reliable. Decrease the number of reads to make automatic detection run faster.
hidden:quantification.assay_type != ‘auto’
default:5000000
quantification.feature_class
label:Feature class
type:basic:string
description:Feature class (3rd column in GTF/GFF3 file) to be used. All other features will be ignored.
hidden:!quantification.show_advanced
default:exon
quantification.feature_type
label:Feature type
type:basic:string
description:The type of feature the quantification program summarizes over (e.g. gene or transcript-level analysis). The value of this parameter needs to be chosen in line with ‘ID attribute’ below.
hidden:!quantification.show_advanced
default:gene
choices:
  • gene: gene
  • transcript: transcript
quantification.id_attribute
label:ID attribute
type:basic:string
description:GTF/GFF3 attribute to be used as feature ID. Several GTF/GFF3 lines with the same feature ID will be considered as parts of the same feature. The feature ID is used to identify the counts in the output table. In GTF files this is usually ‘gene_id’, in GFF3 files this is often ‘ID’, and ‘transcript_id’ is frequently a valid choice for both annotation formats.
hidden:!quantification.show_advanced
default:gene_id
choices:
  • gene_id: gene_id
  • transcript_id: transcript_id
  • ID: ID
  • geneid: geneid
downsampling.n_reads
label:Number of reads
type:basic:integer
default:1000000
downsampling.advanced.seed
label:Seed
type:basic:integer
default:11
downsampling.advanced.fraction
label:Fraction
type:basic:decimal
description:Use the fraction of reads [0 - 1.0] from the orignal input file instead of the absolute number of reads. If set, this will override the “Number of reads” input parameter.
required:False
downsampling.advanced.two_pass
label:2-pass mode
type:basic:boolean
description:Enable two-pass mode when down-sampling. Two-pass mode is twice as slow but with much reduced memory.
default:False
qc.rrna_reference
label:Indexed rRNA reference sequence
type:data:genomeindex:star
description:Reference sequence index prepared by STAR aligner indexing tool.
qc.globin_reference
label:Indexed Globin reference sequence
type:data:genomeindex:star
description:Reference sequence index prepared by STAR aligner indexing tool.

Output results

BED file
data:bedupload-bed (basic:file  src, basic:string  species, basic:string  build)[Source: v1.3.1]

Import a BED file (.bed) which is a tab-delimited text file that defines a feature track. It can have any file extension, but .bed is recommended. The BED file format is described on the [UCSC Genome Bioinformatics web site](http://genome.ucsc.edu/FAQ/FAQformat#format1).

Input arguments

src
label:BED file
type:basic:file
description:Upload BED file annotation track. The first three required BED fields are chrom, chromStart and chromEnd.
required:True
validate_regex:\.(bed|narrowPeak)$
species
label:Species
type:basic:string
description:Species latin name.
choices:
  • Homo sapiens: Homo sapiens
  • Mus musculus: Mus musculus
  • Rattus norvegicus: Rattus norvegicus
  • Dictyostelium discoideum: Dictyostelium discoideum
  • Odocoileus virginianus texanus: Odocoileus virginianus texanus
  • Solanum tuberosum: Solanum tuberosum
build
label:Genome build
type:basic:string

Output results

bed
label:BED file
type:basic:file
bed_jbrowse
label:Bgzip bed file for JBrowse
type:basic:file
tbi_jbrowse
label:Bed file index for Jbrowse
type:basic:file
species
label:Species
type:basic:string
build
label:Build
type:basic:string
BWA ALN
data:alignment:bam:bwaalnalignment-bwa-aln (data:genome:fasta  genome, data:reads:fastq  reads, basic:integer  q, basic:boolean  use_edit, basic:integer  edit_value, basic:decimal  fraction, basic:boolean  seeds, basic:integer  seed_length, basic:integer  seed_dist)[Source: v1.4.2]

Read aligner for mapping low-divergent sequences against a large reference genome. Designed for Illumina sequence reads up to 100bp.

Input arguments

genome
label:Reference genome
type:data:genome:fasta
reads
label:Reads
type:data:reads:fastq
q
label:Quality threshold
type:basic:integer
description:Parameter for dynamic read trimming.
default:0
use_edit
label:Use maximum edit distance (excludes fraction of missing alignments)
type:basic:boolean
default:False
edit_value
label:Maximum edit distance
type:basic:integer
hidden:!use_edit
default:5
fraction
label:Fraction of missing alignments
type:basic:decimal
description:The fraction of missing alignments given 2% uniform base error rate. The maximum edit distance is automatically chosen for different read lengths.
hidden:use_edit
default:0.04
seeds
label:Use seeds
type:basic:boolean
default:False
seed_length
label:Seed length
type:basic:integer
description:Take the first X subsequence as seed. If X is larger than the query sequence, seeding will be disabled. For long reads, this option is typically ranged from 25 to 35 for value 2 in seed maximum edit distance.
hidden:!seeds
default:35
seed_dist
label:Seed maximum edit distance
type:basic:integer
hidden:!seeds
default:2

Output results

bam
label:Alignment file
type:basic:file
description:Position sorted alignment
bai
label:Index BAI
type:basic:file
unmapped
label:Unmapped reads
type:basic:file
required:False
stats
label:Statistics
type:basic:file
bigwig
label:BigWig file
type:basic:file
required:False
species
label:Species
type:basic:string
build
label:Build
type:basic:string
BWA MEM
data:alignment:bam:bwamemalignment-bwa-mem (data:genome:fasta  genome, data:reads:fastq  reads, basic:integer  seed_l, basic:integer  band_w, basic:decimal  re_seeding, basic:boolean  m, basic:integer  match, basic:integer  missmatch, basic:integer  gap_o, basic:integer  gap_e, basic:integer  clipping, basic:integer  unpaired_p, basic:boolean  report_all, basic:integer  report_tr)[Source: v2.2.2]

BWA MEM is a read aligner for mapping low-divergent sequences against a large reference genome. Designed for longer sequences ranged from 70bp to 1Mbp. The algorithm works by seeding alignments with maximal exact matches (MEMs) and then extending seeds with the affine-gap Smith-Waterman algorithm (SW). See [here](http://bio-bwa.sourceforge.net/) for more information.

Input arguments

genome
label:Reference genome
type:data:genome:fasta
reads
label:Reads
type:data:reads:fastq
seed_l
label:Minimum seed length
type:basic:integer
description:Minimum seed length. Matches shorter than minimum seed length will be missed. The alignment speed is usually insensitive to this value unless it significantly deviates 20.
default:19
band_w
label:Band width
type:basic:integer
description:Gaps longer than this will not be found.
default:100
re_seeding
label:Re-seeding factor
type:basic:decimal
description:Trigger re-seeding for a MEM longer than minSeedLen*FACTOR. This is a key heuristic parameter for tuning the performance. Larger value yields fewer seeds, which leads to faster alignment speed but lower accuracy.
default:1.5
m
label:Mark shorter split hits as secondary
type:basic:boolean
description:Mark shorter split hits as secondary (for Picard compatibility)
default:False
scoring.match
label:Score of a match
type:basic:integer
default:1
scoring.missmatch
label:Mismatch penalty
type:basic:integer
default:4
scoring.gap_o
label:Gap open penalty
type:basic:integer
default:6
scoring.gap_e
label:Gap extension penalty
type:basic:integer
default:1
scoring.clipping
label:Clipping penalty
type:basic:integer
description:Clipping is applied if final alignment score is smaller than (best score reaching the end of query) - (Clipping penalty)
default:5
scoring.unpaired_p
label:Penalty for an unpaired read pair
type:basic:integer
description:Affinity to force pair. Score: scoreRead1+scoreRead2-Penalty
default:9
reporting.report_all
label:Report all found alignments
type:basic:boolean
description:Output all found alignments for single-end or unpaired paired-end reads. These alignments will be flagged as secondary alignments.
default:False
reporting.report_tr
label:Report threshold score
type:basic:integer
description:Don’t output alignment with score lower than defined number. This option only affects output.
default:30

Output results

bam
label:Alignment file
type:basic:file
description:Position sorted alignment
bai
label:Index BAI
type:basic:file
unmapped
label:Unmapped reads
type:basic:file
required:False
stats
label:Statistics
type:basic:file
bigwig
label:BigWig file
type:basic:file
required:False
species
label:Species
type:basic:string
build
label:Build
type:basic:string
BWA SW
data:alignment:bam:bwaswalignment-bwa-sw (data:genome:fasta  genome, data:reads:fastq  reads, basic:integer  match, basic:integer  missmatch, basic:integer  gap_o, basic:integer  gap_e)[Source: v1.3.2]

Read aligner for mapping low-divergent sequences against a large reference genome. Designed for longer sequences ranged from 70bp to 1Mbp. The paired-end mode only works for reads Illumina short-insert libraries.

Input arguments

genome
label:Reference genome
type:data:genome:fasta
reads
label:Reads
type:data:reads:fastq
match
label:Score of a match
type:basic:integer
default:1
missmatch
label:Mismatch penalty
type:basic:integer
default:3
gap_o
label:Gap open penalty
type:basic:integer
default:5
gap_e
label:Gap extension penalty
type:basic:integer
default:2

Output results

bam
label:Alignment file
type:basic:file
description:Position sorted alignment
bai
label:Index BAI
type:basic:file
unmapped
label:Unmapped reads
type:basic:file
required:False
stats
label:Statistics
type:basic:file
bigwig
label:BigWig file
type:basic:file
required:False
species
label:Species
type:basic:string
build
label:Build
type:basic:string
Bam split
data:alignment:bam:primarybam-split (data:alignment:bam  bam, data:sam:header  header, data:sam:header  header2)[Source: v0.4.0]

Split hybrid bam file into two bam files.

Input arguments

bam
label:Hybrid alignment bam
type:data:alignment:bam
header
label:Primary header sam file (optional)
type:data:sam:header
description:If no header file is provided, the headers will be extracted from the hybrid alignment bam file.
required:False
header2
label:Secondary header sam file (optional)
type:data:sam:header
description:If no header file is provided, the headers will be extracted from the hybrid alignment bam file.
required:False

Output results

bam
label:Uploaded file
type:basic:file
bai
label:Index BAI
type:basic:file
bigwig
label:BigWig file
type:basic:file
required:False
species
label:Species
type:basic:string
build
label:Build
type:basic:string
Bamliquidator
data:bam:plot:bamliquidatorbamliquidator (basic:string  analysis_type, list:data:alignment:bam  bam, basic:string  cell_type, basic:integer  bin_size, data:annotation:gtf  regions_gtf, data:bed  regions_bed, basic:integer  extension, basic:string  sense, basic:boolean  skip_plot, list:basic:string  black_list, basic:integer  threads)[Source: v0.2.1]

Set of tools for analyzing the density of short DNA sequence read alignments in the BAM file format.

Input arguments

analysis_type
label:Analysis type
type:basic:string
default:bin
choices:
  • Bin mode: bin
  • Region mode: region
  • BED mode: bed
bam
label:BAM File
type:list:data:alignment:bam
cell_type
label:Cell type
type:basic:string
default:cell_type
bin_size
label:Bin size
type:basic:integer
description:Number of base pairs in each bin. The smaller the bin size the longer the runtime and the larger the data files. Default is 100000.
required:False
hidden:analysis_type != ‘bin’
regions_gtf
label:Region gff file / Annotation file (.gff|.gtf)
type:data:annotation:gtf
required:False
hidden:analysis_type != ‘region’
regions_bed
label:Region bed file / Annotation file (.bed)
type:data:bed
required:False
hidden:analysis_type != ‘bed’
extension
label:Extension
type:basic:integer
description:Extends reads by number of bp
default:200
sense
label:Mapping strand to gff file
type:basic:string
default:.
choices:
  • Forward: +
  • Reverse: -
  • Both: .
skip_plot
label:Skip plot
type:basic:boolean
required:False
black_list
label:Black list
type:list:basic:string
description:One or more chromosome patterns to skip during bin liquidation. Default is to skip any chromosomes that contain any of the following substrings chrUn _random Zv9_ _hap.
required:False
threads
label:Threads
type:basic:integer
description:Number of threads to run concurrently during liquidation.
default:1

Output results

analysis_type
label:Analysis type
type:basic:string
hidden:True
output_dir
label:Output directory
type:basic:file
counts
label:Counts HDF5 file
type:basic:file
matrix
label:Matrix file
type:basic:file
required:False
hidden:analysis_type != ‘region’
summary
label:Summary file
type:basic:file:html
required:False
hidden:analysis_type != ‘bin’
Bamplot
data:bam:plot:bamplotbamplot (basic:string  genome, data:annotation:gtf  input_gff, basic:string  input_region, list:data:alignment:bam  bam, basic:integer  stretch_input, basic:string  color, basic:string  sense, basic:integer  extension, basic:boolean  rpm, basic:string  yscale, list:basic:string  names, basic:string  plot, basic:string  title, basic:string  scale, list:data:bed  bed, basic:boolean  multi_page)[Source: v1.3.1]

Plot a single locus from a bam.

Input arguments

genome
label:Genome
type:basic:string
choices:
  • HG19: HG19
  • HG18: HG18
  • MM8: MM8
  • MM9: MM9
  • MM10: MM10
  • RN6: RN6
  • RN4: RN4
input_gff
label:Region string
type:data:annotation:gtf
description:Enter .gff file.
required:False
input_region
label:Region string
type:basic:string
description:Enter genomic region e.g. chr1:+:1-1000.
required:False
bam
label:Bam
type:list:data:alignment:bam
description:bam to plot from
required:False
stretch_input
label:Stretch-input
type:basic:integer
description:Stretch the input regions to a minimum length in bp, e.g. 10000 (for 10kb).
required:False
color
label:Color
type:basic:string
description:Enter a colon separated list of colors e.g. 255,0,0:255,125,0, default samples the rainbow.
default:255,0,0:255,125,0
sense
label:Sense
type:basic:string
description:Map to forward, reverse or’both strands. Default maps to both.
default:both
choices:
  • Forward: forward
  • Reverse: reverse
  • Both: both
extension
label:Extension
type:basic:integer
description:Extends reads by n bp. Default value is 200bp.
default:200
rpm
label:rpm
type:basic:boolean
description:Normalizes density to reads per million (rpm) Default is False.
required:False
yscale
label:y scale
type:basic:string
description:Choose either relative or uniform y axis scaling. Default is relative scaling.
default:relative
choices:
  • relative: relative
  • uniform: uniform
names
label:Names
type:list:basic:string
description:Enter a comma separated list of names for your bams.
required:False
plot
label:Single or multiple polt
type:basic:string
description:Choose either all lines on a single plot or multiple plots.
default:merge
choices:
  • single: single
  • multiple: multiple
  • merge: merge
title
label:Title
type:basic:string
description:Specify a title for the output plot(s), default will be the coordinate region.
default:output
scale
label:Scale
type:basic:string
description:Enter a comma separated list of multiplicative scaling factors for your bams. Default is none.
required:False
bed
label:Bed
type:list:data:bed
description:Add a space-delimited list of bed files to plot.
required:False
multi_page
label:Multi page
type:basic:boolean
description:If flagged will create a new pdf for each region.
default:False

Output results

plot
label:region plot
type:basic:file
BaseSpace file
data:filebasespace-file-import (basic:string  file_id, basic:secret  access_token_secret)[Source: v1.0.3]

Import a file from Illumina BaseSpace.

Input arguments

file_id
label:BaseSpace file ID
type:basic:string
access_token_secret
label:BaseSpace access token
type:basic:secret
description:BaseSpace access token secret handle needed to download the file.

Output results

file
label:File
type:basic:file
Bowtie (Dicty)
data:alignment:bam:bowtie1alignment-bowtie (data:genome:fasta  genome, data:reads:fastq  reads, basic:string  mode, basic:integer  m, basic:integer  l, basic:boolean  use_se, basic:integer  trim_5, basic:integer  trim_3, basic:integer  trim_nucl, basic:integer  trim_iter, basic:string  r)[Source: v1.4.1]

An ultrafast memory-efficient short read aligner.

Input arguments

genome
label:Reference genome
type:data:genome:fasta
reads
label:Reads
type:data:reads:fastq
mode
label:Alignment mode
type:basic:string
description:When the -n option is specified (which is the default), bowtie determines which alignments are valid according to the following policy, which is similar to Maq’s default policy. 1. Alignments may have no more than N mismatches (where N is a number 0-3, set with -n) in the first L bases (where L is a number 5 or greater, set with -l) on the high-quality (left) end of the read. The first L bases are called the “seed”. 2. The sum of the Phred quality values at all mismatched positions (not just in the seed) may not exceed E (set with -e). Where qualities are unavailable (e.g. if the reads are from a FASTA file), the Phred quality defaults to 40. In -v mode, alignments may have no more than V mismatches, where V may be a number from 0 through 3 set using the -v option. Quality values are ignored. The -v option is mutually exclusive with the -n option.
default:-n
choices:
  • Use qualities (-n): -n
  • Use mismatches (-v): -v
m
label:Allowed mismatches
type:basic:integer
description:When used with “Use qualities (-n)” it is the maximum number of mismatches permitted in the “seed”, i.e. the first L base pairs of the read (where L is set with -l/–seedlen). This may be 0, 1, 2 or 3 and the default is 2 When used with “Use mismatches (-v)” report alignments with at most <int> mismatches.
default:2
l
label:Seed length (for -n only)
type:basic:integer
description:Only for “Use qualities (-n)”. Seed length (-l) is the number of bases on the high-quality end of the read to which the -n ceiling applies. The lowest permitted setting is 5 and the default is 28. bowtie is faster for larger values of -l.
default:28
use_se
label:Map as single-ended (for paired end reads only)
type:basic:boolean
description:If this option is selected paired-end reads will be mapped as single-ended.
default:False
start_trimming.trim_5
label:Bases to trim from 5’
type:basic:integer
description:Number of bases to trim from from 5’ (left) end of each read before alignment
default:0
start_trimming.trim_3
label:Bases to trim from 3’
type:basic:integer
description:Number of bases to trim from from 3’ (right) end of each read before alignment
default:0
trimming.trim_nucl
label:Bases to trim
type:basic:integer
description:Number of bases to trim from 3’ end in each iteration.
default:2
trimming.trim_iter
label:Iterations
type:basic:integer
description:Number of iterations.
default:0
reporting.r
label:Reporting mode
type:basic:string
description:Report up to <int> valid alignments per read or pair (-k) (default: 1). Validity of alignments is determined by the alignment policy (combined effects of -n, -v, -l, and -e). If more than one valid alignment exists and the –best and –strata options are specified, then only those alignments belonging to the best alignment “stratum” will be reported. Bowtie is designed to be very fast for small -k but bowtie can become significantly slower as -k increases. If you would like to use Bowtie for larger values of -k, consider building an index with a denser suffix-array sample, i.e. specify a smaller -o/–offrate when invoking bowtie-build for the relevant index (see the Performance tuning section for details).
default:-a -m 1 --best --strata
choices:
  • Report unique alignments: -a -m 1 --best --strata
  • Report all alignments: -a --best
  • Report all alignments in the best stratum: -a --best --strata

Output results

bam
label:Alignment file
type:basic:file
description:Position sorted alignment
bai
label:Index BAI
type:basic:file
unmapped
label:Unmapped reads
type:basic:file
required:False
stats
label:Statistics
type:basic:file
bigwig
label:BigWig file
type:basic:file
required:False
species
label:Species
type:basic:string
build
label:Build
type:basic:string
Bowtie2
data:alignment:bam:bowtie2alignment-bowtie2 (data:genome:fasta  genome, data:reads:fastq  reads, basic:string  mode, basic:string  speed, basic:boolean  use_se, basic:boolean  discordantly, basic:boolean  rep_se, basic:integer  minins, basic:integer  maxins, basic:integer  N, basic:integer  L, basic:integer  gbar, basic:string  mp, basic:string  rdg, basic:string  rfg, basic:string  score_min, basic:integer  trim_5, basic:integer  trim_3, basic:integer  trim_iter, basic:integer  trim_nucl, basic:string  rep_mode, basic:integer  k_reports)[Source: v1.5.0]

Bowtie is an ultrafast, memory-efficient short read aligner. It aligns short DNA sequences (reads) to the human genome at a rate of over 25 million 35-bp reads per hour. Bowtie indexes the genome with a Burrows-Wheeler index to keep its memory footprint small–typically about 2.2 GB for the human genome (2.9 GB for paired-end). See [here](http://bowtie-bio.sourceforge.net/index.shtml) for more information.

Input arguments

genome
label:Reference genome
type:data:genome:fasta
reads
label:Reads
type:data:reads:fastq
mode
label:Alignment mode
type:basic:string
description:End to end: Bowtie 2 requires that the entire read align from one end to the other, without any trimming (or “soft clipping”) of characters from either end. local: Bowtie 2 does not require that the entire read align from one end to the other. Rather, some characters may be omitted (“soft clipped”) from the ends in order to achieve the greatest possible alignment score.
default:--end-to-end
choices:
  • end to end mode: --end-to-end
  • local: --local
speed
label:Speed vs. Sensitivity
type:basic:string
description:A quick setting for aligning fast or accurately. This option is a shortcut for parameters as follows: For –end-to-end: –very-fast -D 5 -R 1 -N 0 -L 22 -i S,0,2.50 –fast -D 10 -R 2 -N 0 -L 22 -i S,0,2.50 –sensitive -D 15 -R 2 -N 0 -L 22 -i S,1,1.15 (default) –very-sensitive -D 20 -R 3 -N 0 -L 20 -i S,1,0.50 For –local: –very-fast-local -D 5 -R 1 -N 0 -L 25 -i S,1,2.00 –fast-local -D 10 -R 2 -N 0 -L 22 -i S,1,1.75 –sensitive-local -D 15 -R 2 -N 0 -L 20 -i S,1,0.75 (default) –very-sensitive-local -D 20 -R 3 -N 0 -L 20 -i S,1,0.50
required:False
choices:
  • Very fast: --very-fast
  • Fast: --fast
  • Sensitive: --sensitive
  • Very sensitive: --very-sensitive
PE_options.use_se
label:Map as single-ended (for paired-end reads only)
type:basic:boolean
description:If this option is selected paired-end reads will be mapped as single-ended and other paired-end options are ignored.
default:False
PE_options.discordantly
label:Report discordantly matched read
type:basic:boolean
description:If both mates have unique alignments, but the alignments do not match paired-end expectations (orientation and relative distance) then alignment will be reported. Useful for detecting structural variations.
default:True
PE_options.rep_se
label:Report single ended
type:basic:boolean
description:If paired alignment can not be found Bowtie2 tries to find alignments for the individual mates.
default:True
PE_options.minins
label:Minimal distance
type:basic:integer
description:The minimum fragment length for valid paired-end alignments. 0 imposes no minimum.
default:0
PE_options.maxins
label:Maximal distance
type:basic:integer
description:The maximum fragment length for valid paired-end alignments.
default:500
alignment_options.N
label:Number of mismatches allowed in seed alignment (N)
type:basic:integer
description:Sets the number of mismatches to allowed in a seed alignment during multiseed alignment. Can be set to 0 or 1. Setting this higher makes alignment slower (often much slower) but increases sensitivity. Default: 0.
required:False
alignment_options.L
label:Length of seed substrings (L)
type:basic:integer
description:Sets the length of the seed substrings to align during multiseed alignment. Smaller values make alignment slower but more sensitive. Default: the –sensitive preset is used by default for end-to-end alignment and –sensitive-local for local alignment. See documentation for details.
required:False
alignment_options.gbar
label:Disallow gaps within positions (gbar)
type:basic:integer
description:Disallow gaps within <int> positions of the beginning or end of the read. Default: 4.
required:False
alignment_options.mp
label:Maximal and minimal mismatch penalty (mp)
type:basic:string
description:Sets the maximum (MX) and minimum (MN) mismatch penalties, both integers. A number less than or equal to MX and greater than or equal to MN is subtracted from the alignment score for each position where a read character aligns to a reference character, the characters do not match, and neither is an N. If –ignore-quals is specified, the number subtracted quals MX. Otherwise, the number subtracted is MN + floor((MX-MN)(MIN(Q, 40.0)/40.0)) where Q is the Phred quality value. Default for MX, MN: 6,2.
required:False
alignment_options.rdg
label:Set read gap open and extend penalties (rdg)
type:basic:string
description:Sets the read gap open (<int1>) and extend (<int2>) penalties. A read gap of length N gets a penalty of <int1> + N * <int2>. Default: 5,3.
required:False
alignment_options.rfg
label:Set reference gap open and close penalties (rfg)
type:basic:string
description:Sets the reference gap open (<int1>) and extend (<int2>) penalties. A reference gap of length N gets a penalty of <int1> + N * <int2>. Default: 5,3.
required:False
alignment_options.score_min
label:Minimum alignment score needed for “valid” alignment (score_min)
type:basic:string
description:Sets a function governing the minimum alignment score needed for an alignment to be considered “valid” (i.e. good enough to report). This is a function of read length. For instance, specifying L,0,-0.6 sets the minimum-score function to f(x) = 0 + -0.6 * x, where x is the read length. The default in –end-to-end mode is L,-0.6,-0.6 and the default in –local mode is G,20,8.
required:False
start_trimming.trim_5
label:Bases to trim from 5’
type:basic:integer
description:Number of bases to trim from from 5’ (left) end of each read before alignment
default:0
start_trimming.trim_3
label:Bases to trim from 3’
type:basic:integer
description:Number of bases to trim from from 3’ (right) end of each read before alignment
default:0
trimming.trim_iter
label:Iterations
type:basic:integer
description:Number of iterations.
default:0
trimming.trim_nucl
label:Bases to trim
type:basic:integer
description:Number of bases to trim from 3’ end in each iteration.
default:2
reporting.rep_mode
label:Report mode
type:basic:string
description:Default mode: search for multiple alignments, report the best one; -k mode: search for one or more alignments, report each; -a mode: search for and report all alignments
default:def
choices:
  • Default mode: def
  • -k mode: k
  • -a mode (very slow): a
reporting.k_reports
label:Number of reports (for -k mode only)
type:basic:integer
description:Searches for at most X distinct, valid alignments for each read. The search terminates when it can’t find more distinct valid alignments, or when it finds X, whichever happens first. default: 5
default:5

Output results

bam
label:Alignment file
type:basic:file
description:Position sorted alignment
bai
label:Index BAI
type:basic:file
unmapped
label:Unmapped reads
type:basic:file
required:False
stats
label:Statistics
type:basic:file
bigwig
label:BigWig file
type:basic:file
required:False
species
label:Species
type:basic:string
build
label:Build
type:basic:string
ChIP-Seq (Gene Score)
data:chipseq:genescorechipseq-genescore (data:chipseq:peakscore  peakscore, basic:decimal  fdr, basic:decimal  pval, basic:decimal  logratio)[Source: v1.1.1]

Chip-Seq analysis - Gene Score (BCM)

Input arguments

peakscore
label:PeakScore file
type:data:chipseq:peakscore
description:PeakScore file
fdr
label:FDR threshold
type:basic:decimal
description:FDR threshold value (default = 0.00005).
default:5e-05
pval
label:Pval threshold
type:basic:decimal
description:Pval threshold value (default = 0.00005).
default:5e-05
logratio
label:Log-ratio threshold
type:basic:decimal
description:Log-ratio threshold value (default = 2).
default:2.0

Output results

genescore
label:Gene Score
type:basic:file
ChIP-Seq (Peak Score)
data:chipseq:peakscorechipseq-peakscore (data:chipseq:callpeak:macs2  peaks, data:bed  bed)[Source: v2.1.0]

Chip-Seq analysis - Peak Score (BCM)

Input arguments

peaks
label:MACS2 results
type:data:chipseq:callpeak:macs2
description:MACS2 results file (NarrowPeak)
bed
label:BED file
type:data:bed

Output results

peak_score
label:Peak Score
type:basic:file
ChIP-seq (MACS2)
data:chipseq:batch:macs2macs2-batch (list:data:alignment:bam  alignments, basic:boolean  advanced, data:bed  promoter, basic:boolean  tagalign, basic:integer  q_threshold, basic:integer  n_sub, basic:boolean  tn5, basic:integer  shift, basic:string  duplicates, basic:string  duplicates_prepeak, basic:decimal  qvalue, basic:decimal  pvalue, basic:decimal  pvalue_prepeak, basic:integer  cap_num, basic:integer  mfold_lower, basic:integer  mfold_upper, basic:integer  slocal, basic:integer  llocal, basic:integer  extsize, basic:integer  shift, basic:integer  band_width, basic:boolean  nolambda, basic:boolean  fix_bimodal, basic:boolean  nomodel, basic:boolean  nomodel_prepeak, basic:boolean  down_sample, basic:boolean  bedgraph, basic:boolean  spmr, basic:boolean  call_summits, basic:boolean  broad, basic:decimal  broad_cutoff)[Source: v1.0.3]

This process runs MACS2 in batch mode. MACS2 analysis is triggered for pairs of samples as defined using treatment-background sample relations. If there are no sample relations defined, each sample is treated individually for the MACS analysis. Model-based Analysis of ChIP-Seq (MACS 2.0), is used to identify transcript factor binding sites. MACS 2.0 captures the influence of genome complexity to evaluate the significance of enriched ChIP regions, and MACS improves the spatial resolution of binding sites through combining the information of both sequencing tag position and orientation. It has also an option to link nearby peaks together in order to call broad peaks. See [here](https://github.com/taoliu/MACS/) for more information. In addition to peak-calling, this process computes ChIP-Seq and ATAC-Seq QC metrics. Process returns a QC metrics report, fragment length estimation, and a deduplicated tagAlign file. QC report contains ENCODE 3 proposed QC metrics – [NRF](https://www.encodeproject.org/data-standards/terms/), [PBC bottlenecking coefficients, NSC, and RSC](https://genome.ucsc.edu/ENCODE/qualityMetrics.html#chipSeq).

Input arguments

alignments
label:Aligned reads
type:list:data:alignment:bam
description:Select multiple treatment/background samples.
advanced
label:Show advanced options
type:basic:boolean
description:Inspect and modify parameters.
default:False
promoter
label:Promoter regions BED file
type:data:bed
description:BED file containing promoter regions (TSS+-1000bp for example). Needed to get the number of peaks and reads mapped to promoter regions.
required:False
hidden:!advanced
tagalign
label:Use tagAlign files
type:basic:boolean
description:Use filtered tagAlign files as case (treatment) and control (background) samples. If extsize parameter is not set, run MACS using input’s estimated fragment length.
hidden:!advanced
default:False
prepeakqc_settings.q_threshold
label:Quality filtering threshold
type:basic:integer
default:30
prepeakqc_settings.n_sub
label:Number of reads to subsample
type:basic:integer
default:15000000
prepeakqc_settings.tn5
label:TN5 shifting
type:basic:boolean
description:Tn5 transposon shifting. Shift reads on “+” strand by 4bp and reads on “-” strand by 5bp.
default:False
prepeakqc_settings.shift
label:User-defined cross-correlation peak strandshift
type:basic:integer
description:If defined, SPP tool will not try to estimate fragment length but will use the given value as fragment length.
required:False
settings.duplicates
label:Number of duplicates
type:basic:string
description:It controls the MACS behavior towards duplicate tags at the exact same location – the same coordination and the same strand. The ‘auto’ option makes MACS calculate the maximum tags at the exact same location based on binomal distribution using 1e-5 as pvalue cutoff and the ‘all’ option keeps all the tags. If an integer is given, at most this number of tags will be kept at the same location. The default is to keep one tag at the same location.
required:False
hidden:tagalign
choices:
  • 1: 1
  • auto: auto
  • all: all
settings.duplicates_prepeak
label:Number of duplicates
type:basic:string
description:It controls the MACS behavior towards duplicate tags at the exact same location – the same coordination and the same strand. The ‘auto’ option makes MACS calculate the maximum tags at the exact same location based on binomal distribution using 1e-5 as pvalue cutoff and the ‘all’ option keeps all the tags. If an integer is given, at most this number of tags will be kept at the same location. The default is to keep one tag at the same location.
required:False
hidden:!tagalign
default:all
choices:
  • 1: 1
  • auto: auto
  • all: all
settings.qvalue
label:Q-value cutoff
type:basic:decimal
description:The q-value (minimum FDR) cutoff to call significant regions. Q-values are calculated from p-values using Benjamini-Hochberg procedure.
required:False
disabled:settings.pvalue && settings.pvalue_prepeak
settings.pvalue
label:P-value cutoff
type:basic:decimal
description:The p-value cutoff. If specified, MACS2 will use p-value instead of q-value cutoff.
required:False
disabled:settings.qvalue
hidden:tagalign
settings.pvalue_prepeak
label:P-value cutoff
type:basic:decimal
description:The p-value cutoff. If specified, MACS2 will use p-value instead of q-value cutoff.
disabled:settings.qvalue
hidden:!tagalign || settings.qvalue
default:1e-05
settings.cap_num
label:Cap number of peaks by taking top N peaks
type:basic:integer
description:To keep all peaks set value to 0.
disabled:settings.broad
default:500000
settings.mfold_lower
label:MFOLD range (lower limit)
type:basic:integer
description:This parameter is used to select the regions within MFOLD range of high-confidence enrichment ratio against background to build model. The regions must be lower than upper limit, and higher than the lower limit of fold enrichment. DEFAULT:10,30 means using all regions not too low (>10) and not too high (<30) to build paired-peaks model. If MACS can not find more than 100 regions to build model, it will use the –extsize parameter to continue the peak detection ONLY if –fix-bimodal is set.
required:False
settings.mfold_upper
label:MFOLD range (upper limit)
type:basic:integer
description:This parameter is used to select the regions within MFOLD range of high-confidence enrichment ratio against background to build model. The regions must be lower than upper limit, and higher than the lower limit of fold enrichment. DEFAULT:10,30 means using all regions not too low (>10) and not too high (<30) to build paired-peaks model. If MACS can not find more than 100 regions to build model, it will use the –extsize parameter to continue the peak detection ONLY if –fix-bimodal is set.
required:False
settings.slocal
label:Small local region
type:basic:integer
description:Slocal and llocal parameters control which two levels of regions will be checked around the peak regions to calculate the maximum lambda as local lambda. By default, MACS considers 1000bp for small local region (–slocal), and 10000bps for large local region (–llocal) which captures the bias from a long range effect like an open chromatin domain. You can tweak these according to your project. Remember that if the region is set too small, a sharp spike in the input data may kill the significant peak.
required:False
settings.llocal
label:Large local region
type:basic:integer
description:Slocal and llocal parameters control which two levels of regions will be checked around the peak regions to calculate the maximum lambda as local lambda. By default, MACS considers 1000bp for small local region (–slocal), and 10000bps for large local region (–llocal) which captures the bias from a long range effect like an open chromatin domain. You can tweak these according to your project. Remember that if the region is set too small, a sharp spike in the input data may kill the significant peak.
required:False
settings.extsize
label:extsize
type:basic:integer
description:While ‘–nomodel’ is set, MACS uses this parameter to extend reads in 5’->3’ direction to fix-sized fragments. For example, if the size of binding region for your transcription factor is 200 bp, and you want to bypass the model building by MACS, this parameter can be set as 200. This option is only valid when –nomodel is set or when MACS fails to build model and –fix-bimodal is on.
required:False
settings.shift
label:Shift
type:basic:integer
description:Note, this is NOT the legacy –shiftsize option which is replaced by –extsize! You can set an arbitrary shift in bp here. Please Use discretion while setting it other than default value (0). When –nomodel is set, MACS will use this value to move cutting ends (5’) then apply –extsize from 5’ to 3’ direction to extend them to fragments. When this value is negative, ends will be moved toward 3’->5’ direction, otherwise 5’->3’ direction. Recommended to keep it as default 0 for ChIP-Seq datasets, or -1 * half of EXTSIZE together with –extsize option for detecting enriched cutting loci such as certain DNAseI-Seq datasets. Note, you can’t set values other than 0 if format is BAMPE for paired-end data. Default is 0.
required:False
settings.band_width
label:Band width
type:basic:integer
description:The band width which is used to scan the genome ONLY for model building. You can set this parameter as the sonication fragment size expected from wet experiment. The previous side effect on the peak detection process has been removed. So this parameter only affects the model building.
required:False
settings.nolambda
label:Use backgroud lambda as local lambda
type:basic:boolean
description:With this flag on, MACS will use the background lambda as local lambda. This means MACS will not consider the local bias at peak candidate regions.
default:False
settings.fix_bimodal
label:Turn on the auto paired-peak model process
type:basic:boolean
description:Whether turn on the auto paired-peak model process. If it’s set, when MACS failed to build paired model, it will use the nomodel settings, the ‘–extsize’ parameter to extend each tags. If set, MACS will be terminated if paired-peak model is failed.
default:False
settings.nomodel
label:Bypass building the shifting model
type:basic:boolean
description:While on, MACS will bypass building the shifting model.
hidden:tagalign
default:False
settings.nomodel_prepeak
label:Bypass building the shifting model
type:basic:boolean
description:While on, MACS will bypass building the shifting model.
hidden:!tagalign
default:True
settings.down_sample
label:Down-sample
type:basic:boolean
description:When set, random sampling method will scale down the bigger sample. By default, MACS uses linear scaling. This option will make the results unstable and irreproducible since each time, random reads would be selected, especially the numbers (pileup, pvalue, qvalue) would change. Consider to use ‘randsample’ script before MACS2 runs instead.
default:False
settings.bedgraph
label:Save fragment pileup and control lambda
type:basic:boolean
description:If this flag is on, MACS will store the fragment pileup, control lambda, -log10pvalue and -log10qvalue scores in bedGraph files. The bedGraph files will be stored in current directory named NAME+’_treat_pileup.bdg’ for treatment data, NAME+’_control_lambda.bdg’ for local lambda values from control, NAME+’_treat_pvalue.bdg’ for Poisson pvalue scores (in -log10(pvalue) form), and NAME+’_treat_qvalue.bdg’ for q-value scores from Benjamini-Hochberg-Yekutieli procedure.
default:True
settings.spmr
label:Save signal per million reads for fragment pileup profiles
type:basic:boolean
disabled:settings.bedgraph === false
default:True
settings.call_summits
label:Call summits
type:basic:boolean
description:MACS will now reanalyze the shape of signal profile (p or q-score depending on cutoff setting) to deconvolve subpeaks within each peak called from general procedure. It’s highly recommended to detect adjacent binding events. While used, the output subpeaks of a big peak region will have the same peak boundaries, and different scores and peak summit positions.
default:False
settings.broad
label:Composite broad regions
type:basic:boolean
description:When this flag is on, MACS will try to composite broad regions in BED12 (a gene-model-like format) by putting nearby highly enriched regions into a broad region with loose cutoff. The broad region is controlled by another cutoff through –broad-cutoff. The maximum length of broad region length is 4 times of d from MACS.
disabled:settings.call_summits === true
default:False
settings.broad_cutoff
label:Broad cutoff
type:basic:decimal
description:Cutoff for broad region. This option is not available unless –broad is set. If -p is set, this is a p-value cutoff, otherwise, it’s a q-value cutoff. DEFAULT = 0.1
required:False
disabled:settings.call_summits === true || settings.broad !== true

Output results

ChIP-seq (MACS2-ROSE2)
data:chipseq:batch:macs2macs2-rose2-batch (list:data:alignment:bam  alignments, basic:boolean  advanced, data:bed  promoter, basic:boolean  tagalign, basic:integer  q_threshold, basic:integer  n_sub, basic:boolean  tn5, basic:integer  shift, basic:string  duplicates, basic:string  duplicates_prepeak, basic:decimal  qvalue, basic:decimal  pvalue, basic:decimal  pvalue_prepeak, basic:integer  cap_num, basic:integer  mfold_lower, basic:integer  mfold_upper, basic:integer  slocal, basic:integer  llocal, basic:integer  extsize, basic:integer  shift, basic:integer  band_width, basic:boolean  nolambda, basic:boolean  fix_bimodal, basic:boolean  nomodel, basic:boolean  nomodel_prepeak, basic:boolean  down_sample, basic:boolean  bedgraph, basic:boolean  spmr, basic:boolean  call_summits, basic:boolean  broad, basic:decimal  broad_cutoff, basic:integer  tss, basic:integer  stitch, data:bed  mask)[Source: v1.0.3]

This process runs MACS2 in batch mode. MACS2 analysis is triggered for pairs of samples as defined using treatment-background sample relations. If there are no sample relations defined, each sample is treated individually for the MACS analysis. Model-based Analysis of ChIP-Seq (MACS 2.0), is used to identify transcript factor binding sites. MACS 2.0 captures the influence of genome complexity to evaluate the significance of enriched ChIP regions, and MACS improves the spatial resolution of binding sites through combining the information of both sequencing tag position and orientation. It has also an option to link nearby peaks together in order to call broad peaks. See [here](https://github.com/taoliu/MACS/) for more information. In addition to peak-calling, this process computes ChIP-Seq and ATAC-Seq QC metrics. Process returns a QC metrics report, fragment length estimation, and a deduplicated tagAlign file. QC report contains ENCODE 3 proposed QC metrics – [NRF](https://www.encodeproject.org/data-standards/terms/), [PBC bottlenecking coefficients, NSC, and RSC](https://genome.ucsc.edu/ENCODE/qualityMetrics.html#chipSeq). For identification of super enhancers R2 uses the Rank Ordering of Super-Enhancers algorithm (ROSE2). This takes the peaks called by RSEG for acetylation and calculates the distances in-between to judge whether they can be considered super-enhancers. The ranked values can be plotted and by locating the inflection point in the resulting graph, super-enhancers can be assigned. It can also be used with the MACS calculated data. See [here](http://younglab.wi.mit.edu/super_enhancer_code.html) for more information.

Input arguments

alignments
label:Aligned reads
type:list:data:alignment:bam
description:Select multiple treatment/background samples.
advanced
label:Show advanced options
type:basic:boolean
description:Inspect and modify parameters.
default:False
promoter
label:Promoter regions BED file
type:data:bed
description:BED file containing promoter regions (TSS+-1000bp for example). Needed to get the number of peaks and reads mapped to promoter regions.
required:False
hidden:!advanced
tagalign
label:Use tagAlign files
type:basic:boolean
description:Use filtered tagAlign files as case (treatment) and control (background) samples. If extsize parameter is not set, run MACS using input’s estimated fragment length.
hidden:!advanced
default:False
prepeakqc_settings.q_threshold
label:Quality filtering threshold
type:basic:integer
default:30
prepeakqc_settings.n_sub
label:Number of reads to subsample
type:basic:integer
default:15000000
prepeakqc_settings.tn5
label:TN5 shifting
type:basic:boolean
description:Tn5 transposon shifting. Shift reads on “+” strand by 4bp and reads on “-” strand by 5bp.
default:False
prepeakqc_settings.shift
label:User-defined cross-correlation peak strandshift
type:basic:integer
description:If defined, SPP tool will not try to estimate fragment length but will use the given value as fragment length.
required:False
settings.duplicates
label:Number of duplicates
type:basic:string
description:It controls the MACS behavior towards duplicate tags at the exact same location – the same coordination and the same strand. The ‘auto’ option makes MACS calculate the maximum tags at the exact same location based on binomal distribution using 1e-5 as pvalue cutoff and the ‘all’ option keeps all the tags. If an integer is given, at most this number of tags will be kept at the same location. The default is to keep one tag at the same location.
required:False
hidden:tagalign
choices:
  • 1: 1
  • auto: auto
  • all: all
settings.duplicates_prepeak
label:Number of duplicates
type:basic:string
description:It controls the MACS behavior towards duplicate tags at the exact same location – the same coordination and the same strand. The ‘auto’ option makes MACS calculate the maximum tags at the exact same location based on binomal distribution using 1e-5 as pvalue cutoff and the ‘all’ option keeps all the tags. If an integer is given, at most this number of tags will be kept at the same location. The default is to keep one tag at the same location.
required:False
hidden:!tagalign
default:all
choices:
  • 1: 1
  • auto: auto
  • all: all
settings.qvalue
label:Q-value cutoff
type:basic:decimal
description:The q-value (minimum FDR) cutoff to call significant regions. Q-values are calculated from p-values using Benjamini-Hochberg procedure.
required:False
disabled:settings.pvalue && settings.pvalue_prepeak
settings.pvalue
label:P-value cutoff
type:basic:decimal
description:The p-value cutoff. If specified, MACS2 will use p-value instead of q-value cutoff.
required:False
disabled:settings.qvalue
hidden:tagalign
settings.pvalue_prepeak
label:P-value cutoff
type:basic:decimal
description:The p-value cutoff. If specified, MACS2 will use p-value instead of q-value cutoff.
disabled:settings.qvalue
hidden:!tagalign || settings.qvalue
default:1e-05
settings.cap_num
label:Cap number of peaks by taking top N peaks
type:basic:integer
description:To keep all peaks set value to 0.
disabled:settings.broad
default:500000
settings.mfold_lower
label:MFOLD range (lower limit)
type:basic:integer
description:This parameter is used to select the regions within MFOLD range of high-confidence enrichment ratio against background to build model. The regions must be lower than upper limit, and higher than the lower limit of fold enrichment. DEFAULT:10,30 means using all regions not too low (>10) and not too high (<30) to build paired-peaks model. If MACS can not find more than 100 regions to build model, it will use the –extsize parameter to continue the peak detection ONLY if –fix-bimodal is set.
required:False
settings.mfold_upper
label:MFOLD range (upper limit)
type:basic:integer
description:This parameter is used to select the regions within MFOLD range of high-confidence enrichment ratio against background to build model. The regions must be lower than upper limit, and higher than the lower limit of fold enrichment. DEFAULT:10,30 means using all regions not too low (>10) and not too high (<30) to build paired-peaks model. If MACS can not find more than 100 regions to build model, it will use the –extsize parameter to continue the peak detection ONLY if –fix-bimodal is set.
required:False
settings.slocal
label:Small local region
type:basic:integer
description:Slocal and llocal parameters control which two levels of regions will be checked around the peak regions to calculate the maximum lambda as local lambda. By default, MACS considers 1000bp for small local region (–slocal), and 10000bps for large local region (–llocal) which captures the bias from a long range effect like an open chromatin domain. You can tweak these according to your project. Remember that if the region is set too small, a sharp spike in the input data may kill the significant peak.
required:False
settings.llocal
label:Large local region
type:basic:integer
description:Slocal and llocal parameters control which two levels of regions will be checked around the peak regions to calculate the maximum lambda as local lambda. By default, MACS considers 1000bp for small local region (–slocal), and 10000bps for large local region (–llocal) which captures the bias from a long range effect like an open chromatin domain. You can tweak these according to your project. Remember that if the region is set too small, a sharp spike in the input data may kill the significant peak.
required:False
settings.extsize
label:extsize
type:basic:integer
description:While ‘–nomodel’ is set, MACS uses this parameter to extend reads in 5’->3’ direction to fix-sized fragments. For example, if the size of binding region for your transcription factor is 200 bp, and you want to bypass the model building by MACS, this parameter can be set as 200. This option is only valid when –nomodel is set or when MACS fails to build model and –fix-bimodal is on.
required:False
settings.shift
label:Shift
type:basic:integer
description:Note, this is NOT the legacy –shiftsize option which is replaced by –extsize! You can set an arbitrary shift in bp here. Please Use discretion while setting it other than default value (0). When –nomodel is set, MACS will use this value to move cutting ends (5’) then apply –extsize from 5’ to 3’ direction to extend them to fragments. When this value is negative, ends will be moved toward 3’->5’ direction, otherwise 5’->3’ direction. Recommended to keep it as default 0 for ChIP-Seq datasets, or -1 * half of EXTSIZE together with –extsize option for detecting enriched cutting loci such as certain DNAseI-Seq datasets. Note, you can’t set values other than 0 if format is BAMPE for paired-end data. Default is 0.
required:False
settings.band_width
label:Band width
type:basic:integer
description:The band width which is used to scan the genome ONLY for model building. You can set this parameter as the sonication fragment size expected from wet experiment. The previous side effect on the peak detection process has been removed. So this parameter only affects the model building.
required:False
settings.nolambda
label:Use backgroud lambda as local lambda
type:basic:boolean
description:With this flag on, MACS will use the background lambda as local lambda. This means MACS will not consider the local bias at peak candidate regions.
default:False
settings.fix_bimodal
label:Turn on the auto paired-peak model process
type:basic:boolean
description:Whether turn on the auto paired-peak model process. If it’s set, when MACS failed to build paired model, it will use the nomodel settings, the ‘–extsize’ parameter to extend each tags. If set, MACS will be terminated if paired-peak model is failed.
default:False
settings.nomodel
label:Bypass building the shifting model
type:basic:boolean
description:While on, MACS will bypass building the shifting model.
hidden:tagalign
default:False
settings.nomodel_prepeak
label:Bypass building the shifting model
type:basic:boolean
description:While on, MACS will bypass building the shifting model.
hidden:!tagalign
default:True
settings.down_sample
label:Down-sample
type:basic:boolean
description:When set, random sampling method will scale down the bigger sample. By default, MACS uses linear scaling. This option will make the results unstable and irreproducible since each time, random reads would be selected, especially the numbers (pileup, pvalue, qvalue) would change. Consider to use ‘randsample’ script before MACS2 runs instead.
default:False
settings.bedgraph
label:Save fragment pileup and control lambda
type:basic:boolean
description:If this flag is on, MACS will store the fragment pileup, control lambda, -log10pvalue and -log10qvalue scores in bedGraph files. The bedGraph files will be stored in current directory named NAME+’_treat_pileup.bdg’ for treatment data, NAME+’_control_lambda.bdg’ for local lambda values from control, NAME+’_treat_pvalue.bdg’ for Poisson pvalue scores (in -log10(pvalue) form), and NAME+’_treat_qvalue.bdg’ for q-value scores from Benjamini-Hochberg-Yekutieli procedure.
default:True
settings.spmr
label:Save signal per million reads for fragment pileup profiles
type:basic:boolean
disabled:settings.bedgraph === false
default:True
settings.call_summits
label:Call summits
type:basic:boolean
description:MACS will now reanalyze the shape of signal profile (p or q-score depending on cutoff setting) to deconvolve subpeaks within each peak called from general procedure. It’s highly recommended to detect adjacent binding events. While used, the output subpeaks of a big peak region will have the same peak boundaries, and different scores and peak summit positions.
default:False
settings.broad
label:Composite broad regions
type:basic:boolean
description:When this flag is on, MACS will try to composite broad regions in BED12 (a gene-model-like format) by putting nearby highly enriched regions into a broad region with loose cutoff. The broad region is controlled by another cutoff through –broad-cutoff. The maximum length of broad region length is 4 times of d from MACS.
disabled:settings.call_summits === true
default:False
settings.broad_cutoff
label:Broad cutoff
type:basic:decimal
description:Cutoff for broad region. This option is not available unless –broad is set. If -p is set, this is a p-value cutoff, otherwise, it’s a q-value cutoff. DEFAULT = 0.1
required:False
disabled:settings.call_summits === true || settings.broad !== true
rose_settings.tss
label:TSS exclusion
type:basic:integer
description:Enter a distance from TSS to exclude. 0 = no TSS exclusion
default:0
rose_settings.stitch
label:Stitch
type:basic:integer
description:Enter a max linking distance for stitching. If not given, optimal stitching parameter will be determined automatically.
required:False
rose_settings.mask
label:Masking BED file
type:data:bed
description:Mask a set of regions from analysis. Provide a BED of masking regions.
required:False

Output results

Chemical Mutagenesis
data:workflow:chemutworkflow-chemut (basic:string  analysis_type, data:genome:fasta  genome, list:data:alignment:bam  parental_strains, list:data:alignment:bam  mutant_strains, basic:boolean  advanced, basic:boolean  br_and_ind_ra, basic:boolean  dbsnp, data:variants:vcf  known_sites, list:data:variants:vcf  known_indels, basic:integer  stand_emit_conf, basic:integer  stand_call_conf, basic:boolean  rf, basic:boolean  advanced, basic:integer  read_depth)[Source: v0.0.6]

Input arguments

analysis_type
label:Analysis type
type:basic:string
description:Choice of the analysis type. Use “SNV” or “INDEL” options to run the GATK analysis only on the haploid portion of the dicty genome. Choose options SNV_CHR2 or INDEL_CHR2 to run the analysis only on the diploid portion of CHR2 (-ploidy 2 -L chr2:2263132-3015703).
default:snv
choices:
  • SNV: snv
  • INDEL: indel
  • SNV_CHR2: snv_chr2
  • INDEL_CHR2: indel_chr2
genome
label:Reference genome
type:data:genome:fasta
parental_strains
label:Parental strains
type:list:data:alignment:bam
mutant_strains
label:Mutant strains
type:list:data:alignment:bam
Vc.advanced
label:Advanced options
type:basic:boolean
required:False
default:False
Vc.br_and_ind_ra
label:Do variant base recalibration and indel realignment
type:basic:boolean
required:False
hidden:Vc.advanced === false
default:False
Vc.dbsnp
label:Use dbSNP file
type:basic:boolean
description:rsIDs from this file are used to populate the ID column of the output. Also, the DB INFO flag will be set when appropriate. dbSNP is not used in any way for the calculations themselves.
required:False
hidden:Vc.advanced === false
default:False
Vc.known_sites
label:Known sites (dbSNP)
type:data:variants:vcf
required:False
hidden:Vc.advanced === false || Vc.br_and_ind_ra === false && Vc.dbsnp === false
Vc.known_indels
label:Known indels
type:list:data:variants:vcf
required:False
hidden:Vc.advanced === false || Vc.br_and_ind_ra === false
default:[]
Vc.stand_emit_conf
label:Emission confidence threshold
type:basic:integer
description:The minimum confidence threshold (phred-scaled) at which the program should emit sites that appear to be possibly variant.
required:False
hidden:Vc.advanced === false
default:10
Vc.stand_call_conf
label:Calling confidence threshold
type:basic:integer
description:The minimum confidence threshold (phred-scaled) at which the program should emit variant sites as called. If a site’s associated genotype has a confidence score lower than the calling threshold, the program will emit the site as filtered and will annotate it as LowQual. This threshold separates high confidence calls from low confidence calls.
required:False
hidden:Vc.advanced === false
default:30
Vc.rf
label:ReasignOneMappingQuality Filter
type:basic:boolean
description:This read transformer will change a certain read mapping quality to a different value without affecting reads that have other mapping qualities. This is intended primarily for users of RNA-Seq data handling programs such as TopHat, which use MAPQ = 255 to designate uniquely aligned reads. According to convention, 255 normally designates “unknown” quality, and most GATK tools automatically ignore such reads. By reassigning a different mapping quality to those specific reads, users of TopHat and other tools can circumvent this problem without affecting the rest of their dataset.
required:False
hidden:Vc.advanced === false
default:False
Vf.advanced
label:Advanced options
type:basic:boolean
required:False
default:False
Vf.read_depth
label:Read depth cutoff
type:basic:integer
description:The minimum number of replicate reads required for a variant site to be included.
required:False
hidden:Vf.advanced === false
default:5

Output results

Convert GFF3 to GTF
data:annotation:gtfgff-to-gtf (data:annotation:gff3  annotation)[Source: v0.3.1]

Convert GFF3 file to GTF format.

Input arguments

annotation
label:Annotation (GFF3)
type:data:annotation:gff3
description:Annotation in GFF3 format.

Output results

annot
label:Converted GTF file
type:basic:file
annot_sorted
label:Sorted GTF file
type:basic:file
annot_sorted_idx_igv
label:Igv index for sorted GTF file
type:basic:file
annot_sorted_track_jbrowse
label:Jbrowse track for sorted GTF
type:basic:file
source
label:Gene ID database
type:basic:string
species
label:Species
type:basic:string
build
label:Build
type:basic:string
Convert files to reads (paired-end)
data:reads:fastq:pairedfiles-to-fastq-paired (list:data:file  src1, list:data:file  src2)[Source: v1.2.1]

Convert FASTQ files to paired-end reads.

Input arguments

src1
label:Mate1
type:list:data:file
src2
label:Mate2
type:list:data:file

Output results

fastq
label:Reads file (mate 1)
type:list:basic:file
fastq2
label:Reads file (mate 2)
type:list:basic:file
fastqc_url
label:Quality control with FastQC (Upstream)
type:list:basic:file:html
fastqc_url2
label:Quality control with FastQC (Downstream)
type:list:basic:file:html
fastqc_archive
label:Download FastQC archive (Upstream)
type:list:basic:file
fastqc_archive2
label:Download FastQC archive (Downstream)
type:list:basic:file
Convert files to reads (single-end)
data:reads:fastq:singlefiles-to-fastq-single (list:data:file  src)[Source: v1.2.1]

Convert FASTQ files to single-end reads.

Input arguments

src
label:Reads
type:list:data:file
description:Sequencing reads in FASTQ format

Output results

fastq
label:Reads file
type:list:basic:file
fastqc_url
label:Quality control with FastQC
type:list:basic:file:html
fastqc_archive
label:Download FastQC archive
type:list:basic:file
Cuffdiff 2.2
data:differentialexpression:cuffdiffcuffdiff (list:data:cufflinks:cuffquant  case, list:data:cufflinks:cuffquant  control, list:basic:string  labels, data:annotation  annotation, data:genome:fasta  genome, basic:boolean  multi_read_correct, basic:decimal  fdr, basic:string  library_type, basic:string  library_normalization, basic:string  dispersion_method)[Source: v2.2.1]

Cuffdiff finds significant changes in transcript expression, splicing, and promoter use. You can use it to find differentially expressed genes and transcripts, as well as genes that are being differentially regulated at the transcriptional and post-transcriptional level. See [here](http://cole-trapnell-lab.github.io/cufflinks/cuffdiff/) and [here](https://software.broadinstitute.org/cancer/software/genepattern/modules/docs/Cuffdiff/7) for more information.

Input arguments

case
label:Case samples
type:list:data:cufflinks:cuffquant
control
label:Control samples
type:list:data:cufflinks:cuffquant
labels
label:Group labels
type:list:basic:string
description:Define labels for each sample group.
default:['control', 'case']
annotation
label:Annotation (GTF/GFF3)
type:data:annotation
description:A transcript annotation file produced by cufflinks, cuffcompare, or other tool.
genome
label:Run bias detection and correction algorithm
type:data:genome:fasta
description:Provide Cufflinks with a multifasta file (genome file) via this option to instruct it to run a bias detection and correction algorithm which can significantly improve accuracy of transcript abundance estimates.
required:False
multi_read_correct
label:Do initial estimation procedure to more accurately weight reads with multiple genome mappings
type:basic:boolean
default:False
fdr
label:Allowed FDR
type:basic:decimal
description:The allowed false discovery rate. The default is 0.05.
default:0.05
library_type
label:Library type
type:basic:string
description:In cases where Cufflinks cannot determine the platform and protocol used to generate input reads, you can supply this information manually, which will allow Cufflinks to infer source strand information with certain protocols. The available options are listed below. For paired-end data, we currently only support protocols where reads are point towards each other: fr-unstranded - Reads from the left-most end of the fragment (in transcript coordinates) map to the transcript strand, and the right-most end maps to the opposite strand; fr-firststrand - Same as above except we enforce the rule that the right-most end of the fragment (in transcript coordinates) is the first sequenced (or only sequenced for single-end reads). Equivalently, it is assumed that only the strand generated during first strand synthesis is sequenced; fr-secondstrand - Same as above except we enforce the rule that the left-most end of the fragment (in transcript coordinates) is the first sequenced (or only sequenced for single-end reads). Equivalently, it is assumed that only the strand generated during second strand synthesis is sequenced.
default:fr-unstranded
choices:
  • fr-unstranded: fr-unstranded
  • fr-firststrand: fr-firststrand
  • fr-secondstrand: fr-secondstrand
library_normalization
label:Library normalization method
type:basic:string
description:You can control how library sizes (i.e. sequencing depths) are normalized in Cufflinks and Cuffdiff. Cuffdiff has several methods that require multiple libraries in order to work. Library normalization methods supported by Cufflinks work on one library at a time.
default:geometric
choices:
  • geometric: geometric
  • classic-fpkm: classic-fpkm
  • quartile: quartile
dispersion_method
label:Dispersion method
type:basic:string
description:Cuffdiff works by modeling the variance in fragment counts across replicates as a function of the mean fragment count across replicates. Strictly speaking, models a quantitity called dispersion - the variance present in a group of samples beyond what is expected from a simple Poisson model of RNA_Seq. You can control how Cuffdiff constructs its model of dispersion in locus fragment counts. Each condition that has replicates can receive its own model, or Cuffdiff can use a global model for all conditions. All of these policies are identical to those used by DESeq (Anders and Huber, Genome Biology, 2010).
default:pooled
choices:
  • pooled: pooled
  • per-condition: per-condition
  • blind: blind
  • poisson: poisson

Output results

raw
label:Differential expression (gene level)
type:basic:file
de_json
label:Results table (JSON)
type:basic:json
de_file
label:Results table (file)
type:basic:file
transcript_diff_exp
label:Differential expression (transcript level)
type:basic:file
tss_group_diff_exp
label:Differential expression (primary transcript)
type:basic:file
cds_diff_exp
label:Differential expression (coding sequence)
type:basic:file
cuffdiff_output
label:Cuffdiff output
type:basic:file
source
label:Gene ID database
type:basic:string
species
label:Species
type:basic:string
build
label:Build
type:basic:string
feature_type
label:Feature type
type:basic:string
Cuffmerge
data:annotation:cuffmergecuffmerge (list:data:cufflinks:cufflinks  expressions, list:data:annotation:gtf  gtf, data:annotation  gff, data:genome:fasta  genome, basic:integer  threads)[Source: v1.3.1]

Cufflinks includes a script called Cuffmerge that you can use to merge together several Cufflinks assemblies. It also handles running Cuffcompare for you, and automatically filters a number of transfrags that are probably artfifacts. The main purpose of Cuffmerge is to make it easier to make an assembly GTF file suitable for use with Cuffdiff. See [here](http://cole-trapnell-lab.github.io/cufflinks/cuffmerge/) for more information.

Input arguments

expressions
label:Cufflinks transcripts (GTF)
type:list:data:cufflinks:cufflinks
required:False
gtf
label:Annotation files (GTF)
type:list:data:annotation:gtf
description:Annotation files you wish to merge together with Cufflinks produced annotation files (e.g. upload Cufflinks annotation GTF file)
required:False
gff
label:Reference annotation (GTF/GFF3)
type:data:annotation
description:An optional “reference” annotation GTF. The input assemblies are merged together with the reference GTF and included in the final output.
required:False
genome
label:Reference genome
type:data:genome:fasta
description:This argument should point to the genomic DNA sequences for the reference. If a directory, it should contain one fasta file per contig. If a multifasta file, all contigs should be present. The merge script will pass this option to cuffcompare, which will use the sequences to assist in classifying transfrags and excluding artifacts (e.g. repeats). For example, Cufflinks transcripts consisting mostly of lower-case bases are classified as repeats. Note that <seq_dir> must contain one fasta file per reference chromosome, and each file must be named after the chromosome, and have a .fa or .fasta extension
required:False
threads
label:Use this many processor threads
type:basic:integer
description:Use this many threads to align reads. The default is 1.
default:1

Output results

annot
label:Merged GTF file
type:basic:file
source
label:Gene ID database
type:basic:string
species
label:Species
type:basic:string
build
label:Build
type:basic:string
Cuffnorm
data:cuffnormcuffnorm (list:data:cufflinks:cuffquant  cuffquant, data:annotation  annotation, basic:boolean  useERCC)[Source: v2.1.3]

Cufflinks includes a program, Cuffnorm, that you can use to generate tables of expression values that are properly normalized for library size. Cuffnorm takes a GTF2/GFF3 file of transcripts as input, along with two or more SAM, BAM, or CXB files for two or more samples. See [here](http://cole-trapnell-lab.github.io/cufflinks/cuffnorm/) for more information. Replicate relation needs to be defined for Cuffnorm to account for replicates. If the replicate relation is not defined, each sample will be treated individually.

Input arguments

cuffquant
label:Cuffquant expression file
type:list:data:cufflinks:cuffquant
annotation
label:Annotation (GTF/GFF3)
type:data:annotation
description:A transcript annotation file produced by cufflinks, cuffcompare, or other source.
useERCC
label:ERCC spike-in normalization
type:basic:boolean
description:Use ERRCC spike-in controls for normalization.
default:False

Output results

genes_count
label:Genes count
type:basic:file
genes_fpkm
label:Genes FPKM
type:basic:file
genes_attr
label:Genes attr table
type:basic:file
isoform_count
label:Isoform count
type:basic:file
isoform_fpkm
label:Isoform FPKM
type:basic:file
isoform_attr
label:Isoform attr table
type:basic:file
cds_count
label:CDS count
type:basic:file
cds_fpkm
label:CDS FPKM
type:basic:file
cds_attr
label:CDS attr table
type:basic:file
tss_groups_count
label:TSS groups count
type:basic:file
tss_groups_fpkm
label:TSS groups FPKM
type:basic:file
tss_attr
label:TSS attr table
type:basic:file
run_info
label:Run info
type:basic:file
raw_scatter
label:FPKM exp scatter plot
type:basic:file
boxplot
label:Boxplot
type:basic:file
fpkm_exp_raw
label:FPKM exp raw
type:basic:file
replicate_correlations
label:Replicate correlatios plot
type:basic:file
fpkm_means
label:FPKM means
type:basic:file
exp_fpkm_means
label:Exp FPKM means
type:basic:file
norm_scatter
label:FKPM exp scatter normalized plot
type:basic:file
required:False
fpkm_exp_norm
label:FPKM exp normalized
type:basic:file
required:False
spike_raw
label:Spike raw
type:basic:file
required:False
spike_norm
label:Spike normalized
type:basic:file
required:False
R_data
label:All R normalization data
type:basic:file
source
label:Gene ID database
type:basic:string
species
label:Species
type:basic:string
build
label:Build
type:basic:string
Cuffquant 2.2
data:cufflinks:cuffquantcuffquant (data:alignment:bam  alignment, data:annotation  annotation, data:genome:fasta  genome, data:annotation:gtf  mask_file, basic:string  library_type, basic:boolean  multi_read_correct)[Source: v1.3.1]

Cuffquant allows you to compute the gene and transcript expression profiles and save these profiles to files that you can analyze later with Cuffdiff or Cuffnorm. See [here](http://cole-trapnell-lab.github.io/cufflinks/manual/) for more information.

Input arguments

alignment
label:Aligned reads
type:data:alignment:bam
annotation
label:Annotation (GTF/GFF3)
type:data:annotation
genome
label:Run bias detection and correction algorithm
type:data:genome:fasta
description:Provide Cufflinks with a multifasta file (genome file) via this option to instruct it to run a bias detection and correction algorithm which can significantly improve accuracy of transcript abundance estimates.
required:False
mask_file
label:Mask file
type:data:annotation:gtf
description:Ignore all reads that could have come from transcripts in this GTF file. We recommend including any annotated rRNA, mitochondrial transcripts other abundant transcripts you wish to ignore in your analysis in this file. Due to variable efficiency of mRNA enrichment methods and rRNA depletion kits, masking these transcripts often improves the overall robustness of transcript abundance estimates.
required:False
library_type
label:Library type
type:basic:string
description:In cases where Cufflinks cannot determine the platform and protocol used to generate input reads, you can supply this information manually, which will allow Cufflinks to infer source strand information with certain protocols. The available options are listed below. For paired-end data, we currently only support protocols where reads are point towards each other: fr-unstranded - Reads from the left-most end of the fragment (in transcript coordinates) map to the transcript strand, and the right-most end maps to the opposite strand; fr-firststrand - Same as above except we enforce the rule that the right-most end of the fragment (in transcript coordinates) is the first sequenced (or only sequenced for single-end reads). Equivalently, it is assumed that only the strand generated during first strand synthesis is sequenced; fr-secondstrand - Same as above except we enforce the rule that the left-most end of the fragment (in transcript coordinates) is the first sequenced (or only sequenced for single-end reads). Equivalently, it is assumed that only the strand generated during second strand synthesis is sequenced.
default:fr-unstranded
choices:
  • fr-unstranded: fr-unstranded
  • fr-firststrand: fr-firststrand
  • fr-secondstrand: fr-secondstrand
multi_read_correct
label:Do initial estimation procedure to more accurately weight reads with multiple genome mappings
type:basic:boolean
description:Run an initial estimation procedure that weights reads mapping to multiple locations more accurately.
default:False

Output results

cxb
label:Abundances (.cxb)
type:basic:file
source
label:Gene ID database
type:basic:string
species
label:Species
type:basic:string
build
label:Build
type:basic:string
Cuffquant results
data:cufflinks:cuffquantupload-cxb (basic:file  src, basic:string  source, basic:string  species, basic:string  build, basic:string  feature_type)[Source: v1.2.1]

Upload Cuffquant results file (.cxb)

Input arguments

src
label:Cuffquant file
type:basic:file
description:Upload Cuffquant results file. Supported extention: *.cxb
required:True
validate_regex:\.(cxb)$
source
label:Gene ID database
type:basic:string
choices:
  • AFFY: AFFY
  • DICTYBASE: DICTYBASE
  • ENSEMBL: ENSEMBL
  • NCBI: NCBI
  • UCSC: UCSC
species
label:Species
type:basic:string
description:Species latin name.
choices:
  • Homo sapiens: Homo sapiens
  • Mus musculus: Mus musculus
  • Rattus norvegicus: Rattus norvegicus
  • Dictyostelium discoideum: Dictyostelium discoideum
  • Odocoileus virginianus texanus: Odocoileus virginianus texanus
  • Solanum tuberosum: Solanum tuberosum
build
label:Build
type:basic:string
feature_type
label:Feature type
type:basic:string
default:gene
choices:
  • gene: gene
  • transcript: transcript
  • exon: exon

Output results

cxb
label:Cuffquant results
type:basic:file
source
label:Gene ID database
type:basic:string
species
label:Species
type:basic:string
build
label:Build
type:basic:string
feature_type
label:Feature type
type:basic:string
Custom master file
data:masterfile:ampliconupload-master-file (basic:file  src, basic:string  panel_name)[Source: v1.1.1]

This should be a tab delimited file (*.txt). Please check the [example](http://genial.is/amplicon-masterfile) file for details.

Input arguments

src
label:Master file
type:basic:file
validate_regex:\.txt(|\.gz|\.bz2|\.tgz|\.tar\.gz|\.tar\.bz2|\.zip|\.rar|\.7z)$
panel_name
label:Panel name
type:basic:string

Output results

master_file
label:Master file
type:basic:file
bedfile
label:BED file (merged targets)
type:basic:file
nomergebed
label:BED file (nonmerged targets)
type:basic:file
olapfreebed
label:BED file (overlap-free targets)
type:basic:file
primers
label:Primers
type:basic:file
panel_name
label:Panel name
type:basic:string
Cutadapt (Diagenode CATS, paired-end)
data:reads:fastq:paired:cutadaptcutadapt-custom-paired (data:reads:fastq:paired  reads)[Source: v1.1.2]

Cutadapt process configured to be used with the Diagenode CATS kits.

Input arguments

reads
label:NGS reads
type:data:reads:fastq:paired

Output results

fastq
label:Reads file (forward)
type:list:basic:file
fastq2
label:Reads file (reverse)
type:list:basic:file
report
label:Cutadapt report
type:basic:file
fastqc_url
label:Quality control with FastQC (forward)
type:list:basic:file:html
fastqc_url2
label:Quality control with FastQC (reverse)
type:list:basic:file:html
fastqc_archive
label:Download FastQC archive (forward)
type:list:basic:file
fastqc_archive2
label:Download FastQC archive (reverse)
type:list:basic:file
Cutadapt (Diagenode CATS, single-end)
data:reads:fastq:single:cutadaptcutadapt-custom-single (data:reads:fastq:single  reads)[Source: v1.1.2]

Cutadapt process configured to be used with the Diagenode CATS kits.

Input arguments

reads
label:NGS reads
type:data:reads:fastq:single

Output results

fastq
label:Reads file
type:list:basic:file
report
label:Cutadapt report
type:basic:file
fastqc_url
label:Quality control with FastQC
type:list:basic:file:html
fastqc_archive
label:Download FastQC archive
type:list:basic:file
Cutadapt (paired-end)
data:reads:fastq:paired:cutadaptcutadapt-paired (data:reads:fastq:paired  reads, data:seq:nucleotide  mate1_5prime_file, data:seq:nucleotide  mate1_3prime_file, data:seq:nucleotide  mate2_5prime_file, data:seq:nucleotide  mate2_3prime_file, list:basic:string  mate1_5prime_seq, list:basic:string  mate1_3prime_seq, list:basic:string  mate2_5prime_seq, list:basic:string  mate2_3prime_seq, basic:integer  times, basic:decimal  error_rate, basic:integer  min_overlap, basic:boolean  match_read_wildcards, basic:integer  leading, basic:integer  trailing, basic:integer  crop, basic:integer  headcrop, basic:integer  minlen, basic:integer  max_n, basic:string  pair_filter)[Source: v2.1.2]

Cutadapt finds and removes adapter sequences, primers, poly-A tails and other types of unwanted sequence from high-throughput sequencing reads. More information about Cutadapt can be found [here](http://cutadapt.readthedocs.io/en/stable/).

Input arguments

reads
label:NGS reads
type:data:reads:fastq:paired
adapters.mate1_5prime_file
label:5 prime adapter file for Mate 1
type:data:seq:nucleotide
required:False
adapters.mate1_3prime_file
label:3 prime adapter file for Mate 1
type:data:seq:nucleotide
required:False
adapters.mate2_5prime_file
label:5 prime adapter file for Mate 2
type:data:seq:nucleotide
required:False
adapters.mate2_3prime_file
label:3 prime adapter file for Mate 2
type:data:seq:nucleotide
required:False
adapters.mate1_5prime_seq
label:5 prime adapter sequence for Mate 1
type:list:basic:string
required:False
adapters.mate1_3prime_seq
label:3 prime adapter sequence for Mate 1
type:list:basic:string
required:False
adapters.mate2_5prime_seq
label:5 prime adapter sequence for Mate 2
type:list:basic:string
required:False
adapters.mate2_3prime_seq
label:3 prime adapter sequence for Mate 2
type:list:basic:string
required:False
adapters.times
label:Times
type:basic:integer
description:Remove up to COUNT adapters from each read.
default:1
adapters.error_rate
label:Error rate
type:basic:decimal
description:Maximum allowed error rate (no. of errors divided by the length of the matching region).
default:0.1
adapters.min_overlap
label:Minimal overlap
type:basic:integer
description:Minimum overlap for an adapter match.
default:3
adapters.match_read_wildcards
label:Match read wildcards
type:basic:boolean
description:Interpret IUPAC wildcards in reads.
default:False
modify_reads.leading
label:Quality on 5 prime
type:basic:integer
description:Remove low quality bases from 5 prime. Specifies the minimum quality required to keep a base.
required:False
modify_reads.trailing
label:Quality on 3 prime
type:basic:integer
description:Remove low quality bases from the 3 prime. Specifies the minimum quality required to keep a base.
required:False
modify_reads.crop
label:Crop
type:basic:integer
description:Cut the specified number of bases from the end of the reads.
required:False
modify_reads.headcrop
label:Headcrop
type:basic:integer
description:Cut the specified number of bases from the start of the reads.
required:False
filtering.minlen
label:Min length
type:basic:integer
description:Drop the read if it is below a specified.
required:False
filtering.max_n
label:Max numebr of N-s
type:basic:integer
description:Discard reads having more ‘N’ bases than specified.
required:False
filtering.pair_filter
label:Which of the reads have to match the filtering criterion
type:basic:string
description:Which of the reads in a paired-end read have to match the filtering criterion in order for the pair to be filtered.
default:any
choices:
  • Any of the reads in a paired-end read have to match the filtering criterion: any
  • Both of the reads in a paired-end read have to match the filtering criterion: both

Output results

fastq
label:Reads file (forward)
type:list:basic:file
fastq2
label:Reads file (reverse)
type:list:basic:file
report
label:Cutadapt report
type:basic:file
fastqc_url
label:Quality control with FastQC (forward)
type:list:basic:file:html
fastqc_url2
label:Quality control with FastQC (reverse)
type:list:basic:file:html
fastqc_archive
label:Download FastQC archive (forward)
type:list:basic:file
fastqc_archive2
label:Download FastQC archive (reverse)
type:list:basic:file
Cutadapt (single-end)
data:reads:fastq:single:cutadaptcutadapt-single (data:reads:fastq:single  reads, data:seq:nucleotide  up_primers_file, data:seq:nucleotide  down_primers_file, list:basic:string  up_primers_seq, list:basic:string  down_primers_seq, basic:integer  polya_tail, basic:integer  leading, basic:integer  trailing, basic:integer  crop, basic:integer  headcrop, basic:integer  min_overlap, basic:integer  minlen, basic:integer  max_n, basic:boolean  match_read_wildcards, basic:integer  times, basic:decimal  error_rate)[Source: v1.2.2]

Cutadapt finds and removes adapter sequences, primers, poly-A tails and other types of unwanted sequence from high-throughput sequencing reads. More information about Cutadapt can be found [here](http://cutadapt.readthedocs.io/en/stable/).

Input arguments

reads
label:NGS reads
type:data:reads:fastq:single
up_primers_file
label:5 prime adapter file
type:data:seq:nucleotide
required:False
down_primers_file
label:3 prime adapter file
type:data:seq:nucleotide
required:False
up_primers_seq
label:5 prime adapter sequence
type:list:basic:string
required:False
down_primers_seq
label:3 prime adapter sequence
type:list:basic:string
required:False
polya_tail
label:Poly-A tail
type:basic:integer
description:Length of poly-A tail, example - AAAN -> 3, AAAAAN -> 5
required:False
leading
label:Quality on 5 prime
type:basic:integer
description:Remove low quality bases from 5 prime. Specifies the minimum quality required to keep a base.
required:False
trailing
label:Quality on 3 prime
type:basic:integer
description:Remove low quality bases from the 3 prime. Specifies the minimum quality required to keep a base.
required:False
crop
label:Crop
type:basic:integer
description:Cut the read to a specified length by removing bases from the end
required:False
headcrop
label:Headcrop
type:basic:integer
description:Cut the specified number of bases from the start of the read
required:False
min_overlap
label:Minimal overlap
type:basic:integer
description:Minimum overlap for an adapter match
default:3
minlen
label:Min length
type:basic:integer
description:Drop the read if it is below a specified length
required:False
max_n
label:Max numebr of N-s
type:basic:integer
description:Discard reads having more ‘N’ bases than specified.
required:False
match_read_wildcards
label:Match read wildcards
type:basic:boolean
description:Interpret IUPAC wildcards in reads.
required:False
default:False
times
label:Times
type:basic:integer
description:Remove up to COUNT adapters from each read.
required:False
default:1
error_rate
label:Error rate
type:basic:decimal
description:Maximum allowed error rate (no. of errors divided by the length of the matching region).
required:False
default:0.1

Output results

fastq
label:Reads file
type:list:basic:file
report
label:Cutadapt report
type:basic:file
fastqc_url
label:Quality control with FastQC
type:list:basic:file:html
fastqc_archive
label:Download FastQC archive
type:list:basic:file
Cutadapt - STAR - HTSeq-count (paired-end)
data:workflow:rnaseq:htseqworkflow-custom-cutadapt-star-htseq-paired (data:reads:fastq:paired  reads, data:genomeindex:star  genome, data:annotation:gtf  gff, basic:string  stranded, basic:boolean  advanced, basic:boolean  noncannonical, basic:boolean  chimeric, basic:integer  chimSegmentMin, basic:boolean  quantmode, basic:boolean  singleend, basic:boolean  gene_counts, basic:string  outFilterType, basic:integer  outFilterMultimapNmax, basic:integer  outFilterMismatchNmax, basic:decimal  outFilterMismatchNoverLmax, basic:integer  alignSJoverhangMin, basic:integer  alignSJDBoverhangMin, basic:integer  alignIntronMin, basic:integer  alignIntronMax, basic:integer  alignMatesGapMax, basic:string  mode, basic:string  feature_class, basic:string  id_attribute, basic:boolean  name_ordered)[Source: v1.0.1]

This RNA-seq pipeline is comprised of three steps, preprocessing, alignment, and quantification. First, reads are preprocessed by __cutadapt__ which finds and removes adapter sequences, primers, poly-A tails and other types of unwanted sequence from high-throughput sequencing reads. Next, preprocessed reads are aligned by __STAR__ aligner. At the time of implementation, STAR is considered a state-of-the-art tool that consistently produces accurate results from diverse sets of reads, and performs well even with default settings. For more information see [this comparison of RNA-seq aligners](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5792058/). Finally, aligned reads are summarized to genes by __HTSeq-count__. Compared to featureCounts, HTSeq-count is not as computationally efficient. All three tools in this workflow support parallelization to accelerate the analysis.

Input arguments

reads
label:NGS reads
type:data:reads:fastq:paired
genome
label:Indexed reference genome
type:data:genomeindex:star
description:Genome index prepared by STAR aligner indexing tool
gff
label:Annotation (GFF)
type:data:annotation:gtf
stranded
label:Assay type
type:basic:string
description:In strand non-specific assay a read is considered overlapping with a feature regardless of whether it is mapped to the same or the opposite strand as the feature. In strand-specific forward assay and single reads, the read has to be mapped to the same strand as the feature. For paired-end reads, the first read has to be on the same strand and the second read on the opposite strand. In strand-specific reverse assay these rules are reversed.
default:no
choices:
  • Strand non-specific: no
  • Strand-specific forward: yes
  • Strand-specific reverse: reverse
advanced
label:Advanced
type:basic:boolean
default:False
star.noncannonical
label:Remove non-cannonical junctions (Cufflinks compatibility)
type:basic:boolean
description:It is recommended to remove the non-canonical junctions for Cufflinks runs using –outFilterIntronMotifs RemoveNoncanonical.
default:False
star.detect_chimeric.chimeric
label:Detect chimeric and circular alignments
type:basic:boolean
description:To switch on detection of chimeric (fusion) alignments (in addition to normal mapping), –chimSegmentMin should be set to a positive value. Each chimeric alignment consists of two “segments”. Each segment is non-chimeric on its own, but the segments are chimeric to each other (i.e. the segments belong to different chromosomes, or different strands, or are far from each other). Both segments may contain splice junctions, and one of the segments may contain portions of both mates. –chimSegmentMin parameter controls the minimum mapped length of the two segments that is allowed. For example, if you have 2x75 reads and used –chimSegmentMin 20, a chimeric alignment with 130b on one chromosome and 20b on the other will be output, while 135 + 15 won’t be.
default:False
star.detect_chimeric.chimSegmentMin
label:–chimSegmentMin
type:basic:integer
disabled:!star.detect_chimeric.chimeric
default:20
star.t_coordinates.quantmode
label:Output in transcript coordinates
type:basic:boolean
description:With –quantMode TranscriptomeSAM option STAR will output alignments translated into transcript coordinates in the Aligned.toTranscriptome.out.bam file (in addition to alignments in genomic coordinates in Aligned.*.sam/bam files). These transcriptomic alignments can be used with various transcript quantification software that require reads to be mapped to transcriptome, such as RSEM or eXpress.
default:False
star.t_coordinates.singleend
label:Allow soft-clipping and indels
type:basic:boolean
description:By default, the output satisfies RSEM requirements: soft-clipping or indels are not allowed. Use –quantTranscriptomeBan Singleend to allow insertions, deletions ans soft-clips in the transcriptomic alignments, which can be used by some expression quantification software (e.g. eXpress).
disabled:!star.t_coordinates.quantmode
default:False
star.t_coordinates.gene_counts
label:Count reads
type:basic:boolean
description:With –quantMode GeneCounts option STAR will count number reads per gene while mapping. A read is counted if it overlaps (1nt or more) one and only one gene. Both ends of the paired-end read are checked for overlaps. The counts coincide with those produced by htseq-count with default parameters. ReadsPerGene.out.tab file with 4 columns which correspond to different strandedness options: column 1: gene ID; column 2: counts for unstranded RNA-seq; column 3: counts for the 1st read strand aligned with RNA (htseq-count option -s yes); column 4: counts for the 2nd read strand aligned with RNA (htseq-count option -s reverse).
disabled:!star.t_coordinates.quantmode
default:False
star.filtering.outFilterType
label:Type of filtering
type:basic:string
description:Normal: standard filtering using only current alignment; BySJout: keep only those reads that contain junctions that passed filtering into SJ.out.tab
default:Normal
choices:
  • Normal: Normal
  • BySJout: BySJout
star.filtering.outFilterMultimapNmax
label:–outFilterMultimapNmax
type:basic:integer
description:Read alignments will be output only if the read maps fewer than this value, otherwise no alignments will be output (default: 10).
required:False
star.filtering.outFilterMismatchNmax
label:–outFilterMismatchNmax
type:basic:integer
description:Alignment will be output only if it has fewer mismatches than this value (default: 10).
required:False
star.filtering.outFilterMismatchNoverLmax
label:–outFilterMismatchNoverLmax
type:basic:decimal
description:Max number of mismatches per pair relative to read length: for 2x100b, max number of mismatches is 0.06*200=8 for the paired read.
required:False
star.alignment.alignSJoverhangMin
label:–alignSJoverhangMin
type:basic:integer
description:Minimum overhang (i.e. block size) for spliced alignments (default: 5).
required:False
star.alignment.alignSJDBoverhangMin
label:–alignSJDBoverhangMin
type:basic:integer
description:Minimum overhang (i.e. block size) for annotated (sjdb) spliced alignments (default: 3).
required:False
star.alignment.alignIntronMin
label:–alignIntronMin
type:basic:integer
description:Minimum intron size: genomic gap is considered intron if its length >= alignIntronMin, otherwise it is considered Deletion (default: 21).
required:False
star.alignment.alignIntronMax
label:–alignIntronMax
type:basic:integer
description:Maximum intron size, if 0, max intron size will be determined by (2pow(winBinNbits)*winAnchorDistNbins) (default: 0).
required:False
star.alignment.alignMatesGapMax
label:–alignMatesGapMax
type:basic:integer
description:Maximum gap between two mates, if 0, max intron gap will be determined by (2pow(winBinNbits)*winAnchorDistNbins) (default: 0).
required:False
htseq.mode
label:Mode
type:basic:string
description:Mode to handle reads overlapping more than one feature. Possible values for <mode> are union, intersection-strict and intersection-nonempty
default:union
choices:
  • union: union
  • intersection-strict: intersection-strict
  • intersection-nonempty: intersection-nonempty
htseq.feature_class
label:Feature class
type:basic:string
description:Feature class (3rd column in GFF file) to be used. All other features will be ignored.
default:exon
htseq.id_attribute
label:ID attribute
type:basic:string
description:GFF attribute to be used as feature ID. Several GFF lines with the same feature ID will be considered as parts of the same feature. The feature ID is used to identity the counts in the output table.
default:gene_id
htseq.name_ordered
label:Use name-ordered BAM file for counting reads
type:basic:boolean
description:Use name-sorted BAM file for reads quantification. Improves compatibility with larger BAM files, but requires more computational time.
required:False
default:False

Output results

Cutadapt - STAR - HTSeq-count (single-end)
data:workflow:rnaseq:htseqworkflow-custom-cutadapt-star-htseq-single (data:reads:fastq:single  reads, data:genomeindex:star  genome, data:annotation:gtf  gff, basic:string  stranded, basic:boolean  advanced, basic:boolean  noncannonical, basic:boolean  chimeric, basic:integer  chimSegmentMin, basic:boolean  quantmode, basic:boolean  singleend, basic:boolean  gene_counts, basic:string  outFilterType, basic:integer  outFilterMultimapNmax, basic:integer  outFilterMismatchNmax, basic:decimal  outFilterMismatchNoverLmax, basic:integer  alignSJoverhangMin, basic:integer  alignSJDBoverhangMin, basic:integer  alignIntronMin, basic:integer  alignIntronMax, basic:integer  alignMatesGapMax, basic:string  mode, basic:string  feature_class, basic:string  id_attribute, basic:boolean  name_ordered)[Source: v1.0.1]

This RNA-seq pipeline is comprised of three steps, preprocessing, alignment, and quantification. First, reads are preprocessed by __cutadapt__ which finds and removes adapter sequences, primers, poly-A tails and other types of unwanted sequence from high-throughput sequencing reads. Next, preprocessed reads are aligned by __STAR__ aligner. At the time of implementation, STAR is considered a state-of-the-art tool that consistently produces accurate results from diverse sets of reads, and performs well even with default settings. For more information see [this comparison of RNA-seq aligners](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5792058/). Finally, aligned reads are summarized to genes by __HTSeq-count__. Compared to featureCounts, HTSeq-count is not as computationally efficient. All three tools in this workflow support parallelization to accelerate the analysis.

Input arguments

reads
label:NGS reads
type:data:reads:fastq:single
genome
label:Indexed reference genome
type:data:genomeindex:star
description:Genome index prepared by STAR aligner indexing tool
gff
label:Annotation (GFF)
type:data:annotation:gtf
stranded
label:Assay type
type:basic:string
description:In strand non-specific assay a read is considered overlapping with a feature regardless of whether it is mapped to the same or the opposite strand as the feature. In strand-specific forward assay and single reads, the read has to be mapped to the same strand as the feature. For paired-end reads, the first read has to be on the same strand and the second read on the opposite strand. In strand-specific reverse assay these rules are reversed.
default:no
choices:
  • Strand non-specific: no
  • Strand-specific forward: yes
  • Strand-specific reverse: reverse
advanced
label:Advanced
type:basic:boolean
default:False
star.noncannonical
label:Remove non-cannonical junctions (Cufflinks compatibility)
type:basic:boolean
description:It is recommended to remove the non-canonical junctions for Cufflinks runs using –outFilterIntronMotifs RemoveNoncanonical.
default:False
star.detect_chimeric.chimeric
label:Detect chimeric and circular alignments
type:basic:boolean
description:To switch on detection of chimeric (fusion) alignments (in addition to normal mapping), –chimSegmentMin should be set to a positive value. Each chimeric alignment consists of two “segments”. Each segment is non-chimeric on its own, but the segments are chimeric to each other (i.e. the segments belong to different chromosomes, or different strands, or are far from each other). Both segments may contain splice junctions, and one of the segments may contain portions of both mates. –chimSegmentMin parameter controls the minimum mapped length of the two segments that is allowed. For example, if you have 2x75 reads and used –chimSegmentMin 20, a chimeric alignment with 130b on one chromosome and 20b on the other will be output, while 135 + 15 won’t be.
default:False
star.detect_chimeric.chimSegmentMin
label:–chimSegmentMin
type:basic:integer
disabled:!star.detect_chimeric.chimeric
default:20
star.t_coordinates.quantmode
label:Output in transcript coordinates
type:basic:boolean
description:With –quantMode TranscriptomeSAM option STAR will output alignments translated into transcript coordinates in the Aligned.toTranscriptome.out.bam file (in addition to alignments in genomic coordinates in Aligned.*.sam/bam files). These transcriptomic alignments can be used with various transcript quantification software that require reads to be mapped to transcriptome, such as RSEM or eXpress.
default:False
star.t_coordinates.singleend
label:Allow soft-clipping and indels
type:basic:boolean
description:By default, the output satisfies RSEM requirements: soft-clipping or indels are not allowed. Use –quantTranscriptomeBan Singleend to allow insertions, deletions ans soft-clips in the transcriptomic alignments, which can be used by some expression quantification software (e.g. eXpress).
disabled:!star.t_coordinates.quantmode
default:False
star.t_coordinates.gene_counts
label:Count reads
type:basic:boolean
description:With –quantMode GeneCounts option STAR will count number reads per gene while mapping. A read is counted if it overlaps (1nt or more) one and only one gene. Both ends of the paired-end read are checked for overlaps. The counts coincide with those produced by htseq-count with default parameters. ReadsPerGene.out.tab file with 4 columns which correspond to different strandedness options: column 1: gene ID; column 2: counts for unstranded RNA-seq; column 3: counts for the 1st read strand aligned with RNA (htseq-count option -s yes); column 4: counts for the 2nd read strand aligned with RNA (htseq-count option -s reverse).
disabled:!star.t_coordinates.quantmode
default:False
star.filtering.outFilterType
label:Type of filtering
type:basic:string
description:Normal: standard filtering using only current alignment; BySJout: keep only those reads that contain junctions that passed filtering into SJ.out.tab
default:Normal
choices:
  • Normal: Normal
  • BySJout: BySJout
star.filtering.outFilterMultimapNmax
label:–outFilterMultimapNmax
type:basic:integer
description:Read alignments will be output only if the read maps fewer than this value, otherwise no alignments will be output (default: 10).
required:False
star.filtering.outFilterMismatchNmax
label:–outFilterMismatchNmax
type:basic:integer
description:Alignment will be output only if it has fewer mismatches than this value (default: 10).
required:False
star.filtering.outFilterMismatchNoverLmax
label:–outFilterMismatchNoverLmax
type:basic:decimal
description:Max number of mismatches per pair relative to read length: for 2x100b, max number of mismatches is 0.06*200=8 for the paired read.
required:False
star.alignment.alignSJoverhangMin
label:–alignSJoverhangMin
type:basic:integer
description:Minimum overhang (i.e. block size) for spliced alignments (default: 5).
required:False
star.alignment.alignSJDBoverhangMin
label:–alignSJDBoverhangMin
type:basic:integer
description:Minimum overhang (i.e. block size) for annotated (sjdb) spliced alignments (default: 3).
required:False
star.alignment.alignIntronMin
label:–alignIntronMin
type:basic:integer
description:Minimum intron size: genomic gap is considered intron if its length >= alignIntronMin, otherwise it is considered Deletion (default: 21).
required:False
star.alignment.alignIntronMax
label:–alignIntronMax
type:basic:integer
description:Maximum intron size, if 0, max intron size will be determined by (2pow(winBinNbits)*winAnchorDistNbins) (default: 0).
required:False
star.alignment.alignMatesGapMax
label:–alignMatesGapMax
type:basic:integer
description:Maximum gap between two mates, if 0, max intron gap will be determined by (2pow(winBinNbits)*winAnchorDistNbins) (default: 0).
required:False
htseq.mode
label:Mode
type:basic:string
description:Mode to handle reads overlapping more than one feature. Possible values for <mode> are union, intersection-strict and intersection-nonempty
default:union
choices:
  • union: union
  • intersection-strict: intersection-strict
  • intersection-nonempty: intersection-nonempty
htseq.feature_class
label:Feature class
type:basic:string
description:Feature class (3rd column in GFF file) to be used. All other features will be ignored.
default:exon
htseq.id_attribute
label:ID attribute
type:basic:string
description:GFF attribute to be used as feature ID. Several GFF lines with the same feature ID will be considered as parts of the same feature. The feature ID is used to identity the counts in the output table.
default:gene_id
htseq.name_ordered
label:Use name-ordered BAM file for counting reads
type:basic:boolean
description:Use name-sorted BAM file for reads quantification. Improves compatibility with larger BAM files, but requires more computational time.
required:False
default:False

Output results

Cutadapt - STAR - RSEM (Diagenode CATS, paired-end)
data:workflow:rnaseq:rsemworkflow-custom-cutadapt-star-rsem-paired (data:reads:fastq:paired  reads, data:genomeindex:star  star_index, data:index:expression  expression_index, basic:string  stranded, basic:boolean  advanced, basic:boolean  noncannonical, basic:boolean  chimeric, basic:integer  chimSegmentMin, basic:boolean  quantmode, basic:boolean  singleend, basic:boolean  gene_counts, basic:string  outFilterType, basic:integer  outFilterMultimapNmax, basic:integer  outFilterMismatchNmax, basic:decimal  outFilterMismatchNoverLmax, basic:integer  alignSJoverhangMin, basic:integer  alignSJDBoverhangMin, basic:integer  alignIntronMin, basic:integer  alignIntronMax, basic:integer  alignMatesGapMax)[Source: v1.0.2]

This RNA-seq pipeline is configured to be used with the Diagenode CATS RNA-seq kits. It is comprised of three steps, preprocessing, alignment, and quantification. First, reads are preprocessed by cutadapt which finds and removes adapter sequences, primers, poly-A tails and other types of unwanted sequence from high-throughput sequencing reads. Next, preprocessed reads are aligned by STAR aligner. Finally, RSEM estimates gene and isoform expression levels from the aligned reads.

Input arguments

reads
label:NGS reads
type:data:reads:fastq:paired
star_index
label:STAR genome index
type:data:genomeindex:star
expression_index
label:Gene expression indices
type:data:index:expression
stranded
label:Assay type
type:basic:string
description:In strand non-specific assay a read is considered overlapping with a feature regardless of whether it is mapped to the same or the opposite strand as the feature. In strand-specific forward assay and single reads, the read has to be mapped to the same strand as the feature. For paired-end reads, the first read has to be on the same strand and the second read on the opposite strand. In strand-specific reverse assay these rules are reversed.
default:no
choices:
  • Strand non-specific: no
  • Strand-specific forward: yes
  • Strand-specific reverse: reverse
advanced
label:Advanced
type:basic:boolean
default:False
star.noncannonical
label:Remove non-cannonical junctions (Cufflinks compatibility)
type:basic:boolean
description:It is recommended to remove the non-canonical junctions for Cufflinks runs using –outFilterIntronMotifs RemoveNoncanonical.
default:False
star.detect_chimeric.chimeric
label:Detect chimeric and circular alignments
type:basic:boolean
description:To switch on detection of chimeric (fusion) alignments (in addition to normal mapping), –chimSegmentMin should be set to a positive value. Each chimeric alignment consists of two “segments”. Each segment is non-chimeric on its own, but the segments are chimeric to each other (i.e. the segments belong to different chromosomes, or different strands, or are far from each other). Both segments may contain splice junctions, and one of the segments may contain portions of both mates. –chimSegmentMin parameter controls the minimum mapped length of the two segments that is allowed. For example, if you have 2x75 reads and used –chimSegmentMin 20, a chimeric alignment with 130b on one chromosome and 20b on the other will be output, while 135 + 15 won’t be.
default:False
star.detect_chimeric.chimSegmentMin
label:–chimSegmentMin
type:basic:integer
disabled:!star.detect_chimeric.chimeric
default:20
star.t_coordinates.quantmode
label:Output in transcript coordinates
type:basic:boolean
description:With –quantMode TranscriptomeSAM option STAR will output alignments translated into transcript coordinates in the Aligned.toTranscriptome.out.bam file (in addition to alignments in genomic coordinates in Aligned.*.sam/bam files). These transcriptomic alignments can be used with various transcript quantification software that require reads to be mapped to transcriptome, such as RSEM or eXpress.
default:True
star.t_coordinates.singleend
label:Allow soft-clipping and indels
type:basic:boolean
description:By default, the output satisfies RSEM requirements: soft-clipping or indels are not allowed. Use –quantTranscriptomeBan Singleend to allow insertions, deletions ans soft-clips in the transcriptomic alignments, which can be used by some expression quantification software (e.g. eXpress).
disabled:!star.t_coordinates.quantmode
default:False
star.t_coordinates.gene_counts
label:Count reads
type:basic:boolean
description:With –quantMode GeneCounts option STAR will count number reads per gene while mapping. A read is counted if it overlaps (1nt or more) one and only one gene. Both ends of the paired-end read are checked for overlaps. The counts coincide with those produced by htseq-count with default parameters. ReadsPerGene.out.tab file with 4 columns which correspond to different strandedness options: column 1: gene ID; column 2: counts for unstranded RNA-seq; column 3: counts for the 1st read strand aligned with RNA (htseq-count option -s yes); column 4: counts for the 2nd read strand aligned with RNA (htseq-count option -s reverse).
disabled:!star.t_coordinates.quantmode
default:False
star.filtering.outFilterType
label:Type of filtering
type:basic:string
description:Normal: standard filtering using only current alignment; BySJout: keep only those reads that contain junctions that passed filtering into SJ.out.tab
default:Normal
choices:
  • Normal: Normal
  • BySJout: BySJout
star.filtering.outFilterMultimapNmax
label:–outFilterMultimapNmax
type:basic:integer
description:Read alignments will be output only if the read maps fewer than this value, otherwise no alignments will be output (default: 10).
required:False
star.filtering.outFilterMismatchNmax
label:–outFilterMismatchNmax
type:basic:integer
description:Alignment will be output only if it has fewer mismatches than this value (default: 10).
required:False
star.filtering.outFilterMismatchNoverLmax
label:–outFilterMismatchNoverLmax
type:basic:decimal
description:Max number of mismatches per pair relative to read length: for 2x100b, max number of mismatches is 0.06*200=8 for the paired read.
required:False
star.alignment.alignSJoverhangMin
label:–alignSJoverhangMin
type:basic:integer
description:Minimum overhang (i.e. block size) for spliced alignments (default: 5).
required:False
star.alignment.alignSJDBoverhangMin
label:–alignSJDBoverhangMin
type:basic:integer
description:Minimum overhang (i.e. block size) for annotated (sjdb) spliced alignments (default: 3).
required:False
star.alignment.alignIntronMin
label:–alignIntronMin
type:basic:integer
description:Minimum intron size: genomic gap is considered intron if its length >= alignIntronMin, otherwise it is considered Deletion (default: 21).
required:False
star.alignment.alignIntronMax
label:–alignIntronMax
type:basic:integer
description:Maximum intron size, if 0, max intron size will be determined by (2pow(winBinNbits)*winAnchorDistNbins) (default: 0).
required:False
star.alignment.alignMatesGapMax
label:–alignMatesGapMax
type:basic:integer
description:Maximum gap between two mates, if 0, max intron gap will be determined by (2pow(winBinNbits)*winAnchorDistNbins) (default: 0).
required:False

Output results

Cutadapt - STAR - RSEM (Diagenode CATS, single-end)
data:workflow:rnaseq:rsemworkflow-custom-cutadapt-star-rsem-single (data:reads:fastq:single  reads, data:genomeindex:star  star_index, data:index:expression  expression_index, basic:string  stranded, basic:boolean  advanced, basic:boolean  noncannonical, basic:boolean  chimeric, basic:integer  chimSegmentMin, basic:boolean  quantmode, basic:boolean  singleend, basic:boolean  gene_counts, basic:string  outFilterType, basic:integer  outFilterMultimapNmax, basic:integer  outFilterMismatchNmax, basic:decimal  outFilterMismatchNoverLmax, basic:integer  alignSJoverhangMin, basic:integer  alignSJDBoverhangMin, basic:integer  alignIntronMin, basic:integer  alignIntronMax, basic:integer  alignMatesGapMax)[Source: v1.0.2]

This RNA-seq pipeline is configured to be used with the Diagenode CATS RNA-seq kits. It is comprised of three steps, preprocessing, alignment, and quantification. First, reads are preprocessed by cutadapt which finds and removes adapter sequences, primers, poly-A tails and other types of unwanted sequence from high-throughput sequencing reads. Next, preprocessed reads are aligned by STAR aligner. Finally, RSEM estimates gene and isoform expression levels from the aligned reads.

Input arguments

reads
label:NGS reads
type:data:reads:fastq:single
star_index
label:STAR genome index
type:data:genomeindex:star
expression_index
label:Gene expression indices
type:data:index:expression
stranded
label:Assay type
type:basic:string
description:In strand non-specific assay a read is considered overlapping with a feature regardless of whether it is mapped to the same or the opposite strand as the feature. In strand-specific forward assay and single reads, the read has to be mapped to the same strand as the feature. For paired-end reads, the first read has to be on the same strand and the second read on the opposite strand. In strand-specific reverse assay these rules are reversed.
default:no
choices:
  • Strand non-specific: no
  • Strand-specific forward: yes
  • Strand-specific reverse: reverse
advanced
label:Advanced
type:basic:boolean
default:False
star.noncannonical
label:Remove non-cannonical junctions (Cufflinks compatibility)
type:basic:boolean
description:It is recommended to remove the non-canonical junctions for Cufflinks runs using –outFilterIntronMotifs RemoveNoncanonical.
default:False
star.detect_chimeric.chimeric
label:Detect chimeric and circular alignments
type:basic:boolean
description:To switch on detection of chimeric (fusion) alignments (in addition to normal mapping), –chimSegmentMin should be set to a positive value. Each chimeric alignment consists of two “segments”. Each segment is non-chimeric on its own, but the segments are chimeric to each other (i.e. the segments belong to different chromosomes, or different strands, or are far from each other). Both segments may contain splice junctions, and one of the segments may contain portions of both mates. –chimSegmentMin parameter controls the minimum mapped length of the two segments that is allowed. For example, if you have 2x75 reads and used –chimSegmentMin 20, a chimeric alignment with 130b on one chromosome and 20b on the other will be output, while 135 + 15 won’t be.
default:False
star.detect_chimeric.chimSegmentMin
label:–chimSegmentMin
type:basic:integer
disabled:!star.detect_chimeric.chimeric
default:20
star.t_coordinates.quantmode
label:Output in transcript coordinates
type:basic:boolean
description:With –quantMode TranscriptomeSAM option STAR will output alignments translated into transcript coordinates in the Aligned.toTranscriptome.out.bam file (in addition to alignments in genomic coordinates in Aligned.*.sam/bam files). These transcriptomic alignments can be used with various transcript quantification software that require reads to be mapped to transcriptome, such as RSEM or eXpress.
default:True
star.t_coordinates.singleend
label:Allow soft-clipping and indels
type:basic:boolean
description:By default, the output satisfies RSEM requirements: soft-clipping or indels are not allowed. Use –quantTranscriptomeBan Singleend to allow insertions, deletions ans soft-clips in the transcriptomic alignments, which can be used by some expression quantification software (e.g. eXpress).
disabled:!star.t_coordinates.quantmode
default:False
star.t_coordinates.gene_counts
label:Count reads
type:basic:boolean
description:With –quantMode GeneCounts option STAR will count number reads per gene while mapping. A read is counted if it overlaps (1nt or more) one and only one gene. Both ends of the paired-end read are checked for overlaps. The counts coincide with those produced by htseq-count with default parameters. ReadsPerGene.out.tab file with 4 columns which correspond to different strandedness options: column 1: gene ID; column 2: counts for unstranded RNA-seq; column 3: counts for the 1st read strand aligned with RNA (htseq-count option -s yes); column 4: counts for the 2nd read strand aligned with RNA (htseq-count option -s reverse).
disabled:!star.t_coordinates.quantmode
default:False
star.filtering.outFilterType
label:Type of filtering
type:basic:string
description:Normal: standard filtering using only current alignment; BySJout: keep only those reads that contain junctions that passed filtering into SJ.out.tab
default:Normal
choices:
  • Normal: Normal
  • BySJout: BySJout
star.filtering.outFilterMultimapNmax
label:–outFilterMultimapNmax
type:basic:integer
description:Read alignments will be output only if the read maps fewer than this value, otherwise no alignments will be output (default: 10).
required:False
star.filtering.outFilterMismatchNmax
label:–outFilterMismatchNmax
type:basic:integer
description:Alignment will be output only if it has fewer mismatches than this value (default: 10).
required:False
star.filtering.outFilterMismatchNoverLmax
label:–outFilterMismatchNoverLmax
type:basic:decimal
description:Max number of mismatches per pair relative to read length: for 2x100b, max number of mismatches is 0.06*200=8 for the paired read.
required:False
star.alignment.alignSJoverhangMin
label:–alignSJoverhangMin
type:basic:integer
description:Minimum overhang (i.e. block size) for spliced alignments (default: 5).
required:False
star.alignment.alignSJDBoverhangMin
label:–alignSJDBoverhangMin
type:basic:integer
description:Minimum overhang (i.e. block size) for annotated (sjdb) spliced alignments (default: 3).
required:False
star.alignment.alignIntronMin
label:–alignIntronMin
type:basic:integer
description:Minimum intron size: genomic gap is considered intron if its length >= alignIntronMin, otherwise it is considered Deletion (default: 21).
required:False
star.alignment.alignIntronMax
label:–alignIntronMax
type:basic:integer
description:Maximum intron size, if 0, max intron size will be determined by (2pow(winBinNbits)*winAnchorDistNbins) (default: 0).
required:False
star.alignment.alignMatesGapMax
label:–alignMatesGapMax
type:basic:integer
description:Maximum gap between two mates, if 0, max intron gap will be determined by (2pow(winBinNbits)*winAnchorDistNbins) (default: 0).
required:False

Output results

DESeq2
data:differentialexpression:deseq2differentialexpression-deseq2 (list:data:expression  case, list:data:expression  control, basic:boolean  count, basic:integer  min_count_sum, basic:boolean  cook, basic:decimal  cooks_cutoff, basic:boolean  independent, basic:decimal  alpha)[Source: v2.2.0]

The DESeq2 package estimates variance-mean dependence in count data from high-throughput sequencing assays and tests for differential expression based on a model using the negative binomial distribution. See [here](https://www.bioconductor.org/packages/release/bioc/manuals/DESeq2/man/DESeq2.pdf) and [here](http://bioconductor.org/packages/devel/bioc/vignettes/DESeq2/inst/doc/DESeq2.html) for more information.

Input arguments

case
label:Case
type:list:data:expression
description:Case samples (replicates)
control
label:Control
type:list:data:expression
description:Control samples (replicates)
filter.count
label:Filter genes based on expression count
type:basic:boolean
default:True
filter.min_count_sum
label:Minimum raw gene expression count summed over all samples
type:basic:integer
description:Filter genes in the expression matrix input. Remove genes where the expression count sum over all samples is below the threshold.
hidden:!filter.count
default:10
filter.cook
label:Filter genes based on Cook’s distance
type:basic:boolean
default:False
filter.cooks_cutoff
label:Threshold on Cook’s distance
type:basic:decimal
description:If one or more samples have Cook’s distance larger than the threshold set here, the p-value for the row is set to NA. If left empty, the default threshold of 0.99 quantile of the F(p, m-p) distribution is used, where p is the number of coefficients being fitted and m is the number of samples. This test excludes Cook’s distance of samples belonging to experimental groups with only two samples.
required:False
hidden:!filter.cook
filter.independent
label:Apply independent gene filtering
type:basic:boolean
default:False
filter.alpha
label:Significance cut-off used for optimizing independent gene filtering
type:basic:decimal
description:The value should be set to adjusted p-value cut-off (FDR).
hidden:!filter.independent
default:0.1

Output results

raw
label:Differential expression
type:basic:file
de_json
label:Results table (JSON)
type:basic:json
de_file
label:Results table (file)
type:basic:file
count_matrix
label:Count matrix
type:basic:file
source
label:Gene ID database
type:basic:string
species
label:Species
type:basic:string
build
label:Build
type:basic:string
feature_type
label:Feature type
type:basic:string
Detect library strandedness
data:strandednesslibrary-strandedness (data:reads:fastq  reads, basic:integer  read_number, data:index:salmon  salmon_index)[Source: v0.1.2]

This process uses the Salmon transcript quantification tool to automatically infer the NGS library strandedness. For more details, please see the Salmon [documentation](https://salmon.readthedocs.io/en/latest/library_type.html)

Input arguments

reads
label:Sequencing reads
type:data:reads:fastq
description:Sequencing reads in .fastq format. Both single and paired-end libraries are supported
read_number
label:Number of input reads
type:basic:integer
description:Number of sequencing reads that are subsampled from each of the original .fastq files before library strand detection
default:50000
salmon_index
label:Transcriptome index file
type:data:index:salmon
description:Transcriptome index file created using the Salmon indexing tool. cDNA (transcriptome) sequences used for index file creation must be derived from the same species as the input sequencing reads to obtain the reliable analysis results

Output results

strandedness
label:Library strandedness type
type:basic:string
description:The predicted library strandedness type. The codes U and IU indicate ‘strand non-specific’ library for single or paired-end reads, respectively. Codes SF and ISF correspond to the ‘strand-specific forward’ library, for the single or paired-end reads, respectively. For ‘strand-specific reverse’ library, the corresponding codes are SR and ISR. For more details, please see the Salmon [documentation](https://salmon.readthedocs.io/en/latest/library_type.html)
fragment_ratio
label:Compatible fragment ratio
type:basic:decimal
description:The ratio of fragments that support the predicted library strandedness type
log
label:Log file
type:basic:file
description:Analysis log file.
Dictyostelium expressions
data:expression:polyaexpression-dicty (data:alignment:bam  alignment, data:annotation:gff3  gff, data:mappability:bcm  mappable)[Source: v1.3.1]

Dictyostelium-specific pipeline. Developed by Bioinformatics Laboratory, Faculty of Computer and Information Science, University of Ljubljana, Slovenia and Shaulsky Lab, Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA.

Input arguments

alignment
label:Aligned sequence
type:data:alignment:bam
gff
label:Features (GFF3)
type:data:annotation:gff3
mappable
label:Mappability
type:data:mappability:bcm

Output results

exp
label:Expression RPKUM (polyA)
type:basic:file
description:mRNA reads scaled by uniquely mappable part of exons.
rpkmpolya
label:Expression RPKM (polyA)
type:basic:file
description:mRNA reads scaled by exon length.
rc
label:Read counts (polyA)
type:basic:file
description:mRNA reads uniquely mapped to gene exons.
rpkum
label:Expression RPKUM
type:basic:file
description:Reads scaled by uniquely mappable part of exons.
rpkm
label:Expression RPKM
type:basic:file
description:Reads scaled by exon length.
rc_raw
label:Read counts (raw)
type:basic:file
description:Reads uniquely mapped to gene exons.
exp_json
label:Expression RPKUM (polyA) (json)
type:basic:json
exp_type
label:Expression Type (default output)
type:basic:string
source
label:Gene ID database
type:basic:string
species
label:Species
type:basic:string
build
label:Build
type:basic:string
feature_type
label:Feature type
type:basic:string
Differential Expression (table)
data:differentialexpression:uploadupload-diffexp (basic:file  src, basic:string  gene_id, basic:string  logfc, basic:string  fdr, basic:string  logodds, basic:string  fwer, basic:string  pvalue, basic:string  stat, basic:string  source, basic:string  species, basic:string  build, basic:string  feature_type, list:data:expression  case, list:data:expression  control)[Source: v1.2.1]

Upload Differential Expression table.

Input arguments

src
label:Differential expression file
type:basic:file
description:Differential expression file. Supported file types: *.xls, *.xlsx, *.tab (tab-delimited file), *.diff. DE file must include columns with log2(fold change) and FDR or pval information. DE file must contain header row with column names. Accepts DESeq, DESeq2, edgeR and CuffDiff output files.
validate_regex:\.(xls|xlsx|tab|tab.gz|diff|diff.gz)$
gene_id
label:Gene ID label
type:basic:string
logfc
label:LogFC label
type:basic:string
fdr
label:FDR label
type:basic:string
required:False
logodds
label:LogOdds label
type:basic:string
required:False
fwer
label:FWER label
type:basic:string
required:False
pvalue
label:Pvalue label
type:basic:string
required:False
stat
label:Statistics label
type:basic:string
required:False
source
label:Gene ID database
type:basic:string
choices:
  • AFFY: AFFY
  • DICTYBASE: DICTYBASE
  • ENSEMBL: ENSEMBL
  • NCBI: NCBI
  • UCSC: UCSC
species
label:Species
type:basic:string
description:Species latin name.
choices:
  • Homo sapiens: Homo sapiens
  • Mus musculus: Mus musculus
  • Rattus norvegicus: Rattus norvegicus
  • Dictyostelium discoideum: Dictyostelium discoideum
  • Odocoileus virginianus texanus: Odocoileus virginianus texanus
  • Solanum tuberosum: Solanum tuberosum
build
label:Build
type:basic:string
description:Genome build or annotation version.
feature_type
label:Feature type
type:basic:string
default:gene
choices:
  • gene: gene
  • transcript: transcript
  • exon: exon
case
label:Case
type:list:data:expression
description:Case samples (replicates)
required:False
control
label:Control
type:list:data:expression
description:Control samples (replicates)
required:False

Output results

raw
label:Differential expression
type:basic:file
de_json
label:Results table (JSON)
type:basic:json
de_file
label:Results table (file)
type:basic:file
source
label:Gene ID database
type:basic:string
species
label:Species
type:basic:string
build
label:Build
type:basic:string
feature_type
label:Feature type
type:basic:string
Expression Time Course
data:etcetc-bcm (list:data:expression  expressions, basic:boolean  avg)[Source: v1.1.1]

Select gene expression data and form a time course.

Input arguments

expressions
label:RPKM expression profile
type:list:data:expression
required:True
avg
label:Average by time
type:basic:boolean
default:True

Output results

etcfile
label:Expression time course file
type:basic:file
etc
label:Expression time course
type:basic:json
Expression aggregator
data:aggregator:expressionexpression-aggregator (list:data:expression  exps, basic:string  group_by, data:aggregator:expression  expr_aggregator)[Source: v0.2.2]

Collect expression data from samples grouped by sample descriptor field. The Expression aggregator process should not be run in Batch Mode, as this will create redundant outputs. Rather, select multiple samples below for which you wish to aggregate the expression matrix.

Input arguments

exps
label:Expressions
type:list:data:expression
group_by
label:Sample descriptor field
type:basic:string
expr_aggregator
label:Expression aggregator
type:data:aggregator:expression
required:False

Output results

exp_matrix
label:Expression matrix
type:basic:file
box_plot
label:Box plot
type:basic:json
log_box_plot
label:Log box plot
type:basic:json
source
label:Gene ID database
type:basic:string
species
label:Species
type:basic:string
exp_type
label:Expression type
type:basic:string
Expression data
data:expressionupload-expression (basic:file  rc, basic:file  exp, basic:string  exp_name, basic:string  exp_type, basic:string  source, basic:string  species, basic:string  build, basic:string  feature_type)[Source: v2.2.1]

Upload expression data by providing raw expression data (read counts) and/or normalized expression data together with the associated data normalization type.

Input arguments

rc
label:Read counts (raw expression)
type:basic:file
description:Reads mapped to genomic features (raw count data). Supported extensions: .txt.gz (preferred), .tab.* or .txt.*
required:False
validate_regex:\.(txt|tab|gz)(|\.gz|\.bz2|\.tgz|\.tar\.gz|\.tar\.bz2|\.zip|\.rar|\.7z)$
exp
label:Normalized expression
type:basic:file
description:Normalized expression data. Supported extensions: .tab.gz (preferred) or .tab.*
required:False
validate_regex:\.(tab|gz)(|\.gz|\.bz2|\.tgz|\.tar\.gz|\.tar\.bz2|\.zip|\.rar|\.7z)$
exp_name
label:Expression name
type:basic:string
exp_type
label:Normalization type
type:basic:string
description:Normalization type
required:False
source
label:Gene ID source
type:basic:string
choices:
  • AFFY: AFFY
  • DICTYBASE: DICTYBASE
  • ENSEMBL: ENSEMBL
  • NCBI: NCBI
  • UCSC: UCSC
species
label:Species
type:basic:string
description:Species latin name.
choices:
  • Homo sapiens: Homo sapiens
  • Mus musculus: Mus musculus
  • Rattus norvegicus: Rattus norvegicus
  • Dictyostelium discoideum: Dictyostelium discoideum
  • Odocoileus virginianus texanus: Odocoileus virginianus texanus
  • Solanum tuberosum: Solanum tuberosum
build
label:Build
type:basic:string
description:Genome build or annotation version.
feature_type
label:Feature type
type:basic:string
default:gene
choices:
  • gene: gene
  • transcript: transcript
  • exon: exon

Output results

exp
label:Normalized expression
type:basic:file
description:Normalized expression
rc
label:Read counts
type:basic:file
description:Reads mapped to genomic features.
required:False
exp_json
label:Expression (json)
type:basic:json
exp_type
label:Expression type
type:basic:string
exp_set
label:Expressions
type:basic:file
exp_set_json
label:Expressions (json)
type:basic:json
source
label:Gene ID source
type:basic:string
species
label:Species
type:basic:string
build
label:Build
type:basic:string
feature_type
label:Feature type
type:basic:string
Expression data (Cuffnorm)
data:expressionupload-expression-cuffnorm (basic:file  exp, data:cufflinks:cuffquant  cxb, basic:string  exp_type)[Source: v1.4.1]

Upload expression data by providing Cuffnorm results.

Input arguments

exp
label:Normalized expression
type:basic:file
cxb
label:Cuffquant analysis
type:data:cufflinks:cuffquant
description:Cuffquant analysis.
exp_type
label:Normalization type
type:basic:string
default:Cuffnorm

Output results

exp
label:Normalized expression
type:basic:file
description:Normalized expression
rc
label:Read counts
type:basic:file
description:Reads mapped to genomic features.
required:False
exp_json
label:Expression (json)
type:basic:json
exp_type
label:Expression type
type:basic:string
exp_set
label:Expressions
type:basic:file
exp_set_json
label:Expressions (json)
type:basic:json
source
label:Gene ID source
type:basic:string
species
label:Species
type:basic:string
build
label:Build
type:basic:string
feature_type
label:Feature type
type:basic:string
Expression data (STAR)
data:expression:starupload-expression-star (basic:file  rc, basic:string  stranded, basic:string  source, basic:string  species, basic:string  build, basic:string  feature_type)[Source: v1.3.1]

Upload expression data by providing STAR aligner results.

Input arguments

rc
label:Read counts (raw expression)
type:basic:file
description:Reads mapped to genomic features (raw count data). Supported extensions: .txt.gz (preferred), .tab.* or .txt.*
validate_regex:\.(txt|tab|gz)(|\.gz|\.bz2|\.tgz|\.tar\.gz|\.tar\.bz2|\.zip|\.rar|\.7z)$
stranded
label:Is data from a strand specific assay?
type:basic:string
description:For stranded=no, a read is considered overlapping with a feature regardless of whether it is mapped to the same or the opposite strand as the feature. For stranded=yes and single-end reads, the read has to be mapped to the same strand as the feature. For paired-end reads, the first read has to be on the same strand and the second read on the opposite strand. For stranded=reverse, these rules are reversed.
default:yes
choices:
  • yes: yes
  • no: no
  • reverse: reverse
source
label:Gene ID source
type:basic:string
choices:
  • AFFY: AFFY
  • DICTYBASE: DICTYBASE
  • ENSEMBL: ENSEMBL
  • NCBI: NCBI
  • UCSC: UCSC
species
label:Species
type:basic:string
description:Species latin name.
choices:
  • Homo sapiens: Homo sapiens
  • Mus musculus: Mus musculus
  • Rattus norvegicus: Rattus norvegicus
  • Dictyostelium discoideum: Dictyostelium discoideum
  • Odocoileus virginianus texanus: Odocoileus virginianus texanus
  • Solanum tuberosum: Solanum tuberosum
build
label:Build
type:basic:string
description:Genome build or annotation version.
feature_type
label:Feature type
type:basic:string
default:gene
choices:
  • gene: gene
  • transcript: transcript
  • exon: exon

Output results

rc
label:Read counts (raw data)
type:basic:file
description:Reads mapped to genomic features.
exp
label:Expression data
type:basic:file
exp_json
label:Expression (json)
type:basic:json
exp_type
label:Expression type
type:basic:string
exp_set
label:Expressions
type:basic:file
exp_set_json
label:Expressions (json)
type:basic:json
source
label:Gene ID source
type:basic:string
species
label:Species
type:basic:string
build
label:Build
type:basic:string
feature_type
label:Feature type
type:basic:string
Expression matrix
data:expressionsetmergeexpressions (list:data:expression  exps, list:basic:string  genes)[Source: v1.1.1]

Merge expression data to create an expression matrix where each column represents all the gene expression levels from a single experiment, and each row represents the expression of a gene across all experiments.

Input arguments

exps
label:Gene expressions
type:list:data:expression
genes
label:Filter genes
type:list:basic:string
required:False

Output results

expset
label:Expression set
type:basic:file
expset_type
label:Expression set type
type:basic:string
Expression time course
data:etcupload-etc (basic:file  src)[Source: v1.1.1]

Upload Expression time course.

Input arguments

src
label:Expression time course file (xls or tab)
type:basic:file
description:Expression time course
required:True
validate_regex:\.(xls|xlsx|tab)$

Output results

etcfile
label:Expression time course file
type:basic:file
etc
label:Expression time course
type:basic:json
FASTA file
data:seq:nucleotideupload-fasta-nucl (basic:file  src, basic:string  species, basic:string  build, basic:string  source)[Source: v2.0.0]

Import a FASTA file, which is a text-based format for representing either nucleotide sequences or peptide sequences, in which nucleotides or amino acids are represented using single-letter codes.

Input arguments

src
label:Sequence file (FASTA)
type:basic:file
description:Sequence file (containing single or multiple sequences) in FASTA format. Supported extensions: .fasta.gz (preferred), .fa.*, .fna.* or .fasta.*
validate_regex:\.(fasta|fa|fna)(|\.gz|\.bz2|\.tgz|\.tar\.gz|\.tar\.bz2|\.zip|\.rar|\.7z)$
species
label:Species
type:basic:string
description:Species latin name.
required:False
choices:
  • Homo sapiens: Homo sapiens
  • Mus musculus: Mus musculus
  • Rattus norvegicus: Rattus norvegicus
  • Dictyostelium discoideum: Dictyostelium discoideum
build
label:Genome build
type:basic:string
required:False
source
label:Database source
type:basic:string
required:False

Output results

fastagz
label:FASTA file (compressed)
type:basic:file
fasta
label:FASTA file
type:basic:file
fai
label:FASTA file index
type:basic:file
number
label:Number of sequences
type:basic:integer
species
label:Species
type:basic:string
required:False
source
label:Database source
type:basic:string
required:False
build
label:Build
type:basic:string
required:False
FASTQ file (paired-end)
data:reads:fastq:pairedupload-fastq-paired (list:basic:file  src1, list:basic:file  src2)[Source: v2.2.1]

Import paired-end reads in FASTQ format, which is a text-based format for storing both a biological sequence (usually nucleotide sequence) and its corresponding quality scores.

Input arguments

src1
label:Mate1
type:list:basic:file
description:Sequencing reads in FASTQ format. Supported extensions: .fastq.gz (preferred), .fq.* or .fastq.*
validate_regex:(\.(fastq|fq)(|\.gz|\.bz2|\.tgz|\.tar\.gz|\.tar\.bz2|\.zip|\.rar|\.7z))|(\.bz2)$
src2
label:Mate2
type:list:basic:file
description:Sequencing reads in FASTQ format. Supported extensions: .fastq.gz (preferred), .fq.* or .fastq.*
validate_regex:(\.(fastq|fq)(|\.gz|\.bz2|\.tgz|\.tar\.gz|\.tar\.bz2|\.zip|\.rar|\.7z))|(\.bz2)$

Output results

fastq
label:Reads file (mate 1)
type:list:basic:file
fastq2
label:Reads file (mate 2)
type:list:basic:file
fastqc_url
label:Quality control with FastQC (Upstream)
type:list:basic:file:html
fastqc_url2
label:Quality control with FastQC (Downstream)
type:list:basic:file:html
fastqc_archive
label:Download FastQC archive (Upstream)
type:list:basic:file
fastqc_archive2
label:Download FastQC archive (Downstream)
type:list:basic:file
FASTQ file (single-end)
data:reads:fastq:singleupload-fastq-single (list:basic:file  src)[Source: v2.2.1]

Import single-end reads in FASTQ format, which is a text-based format for storing both a biological sequence (usually nucleotide sequence) and its corresponding quality scores.

Input arguments

src
label:Reads
type:list:basic:file
description:Sequencing reads in FASTQ format. Supported extensions: .fastq.gz (preferred), .fq.* or .fastq.*
validate_regex:(\.(fastq|fq)(|\.gz|\.bz2|\.tgz|\.tar\.gz|\.tar\.bz2|\.zip|\.rar|\.7z))|(\.bz2)$

Output results

fastq
label:Reads file
type:list:basic:file
fastqc_url
label:Quality control with FastQC
type:list:basic:file:html
fastqc_archive
label:Download FastQC archive
type:list:basic:file
GAF file
data:gaf:2:0upload-gaf (basic:file  src, basic:string  source, basic:string  species)[Source: v1.1.1]

GO annotation file (GAF v2.0) relating gene ID and associated GO terms

Input arguments

src
label:GO annotation file (GAF v2.0)
type:basic:file
description:Upload GO annotation file (GAF v2.0) relating gene ID and associated GO terms
source
label:Gene ID database
type:basic:string
choices:
  • AFFY: AFFY
  • DICTYBASE: DICTYBASE
  • ENSEMBL: ENSEMBL
  • MGI: MGI
  • NCBI: NCBI
  • UCSC: UCSC
  • UniProtKB: UniProtKB
species
label:Species
type:basic:string

Output results

gaf
label:GO annotation file (GAF v2.0)
type:basic:file
gaf_obj
label:GAF object
type:basic:file
source
label:Gene ID database
type:basic:string
species
label:Species
type:basic:string
GATK3 (HaplotypeCaller)
data:variants:vcf:gatk:hcvc-gatk-hc (data:alignment:bam  alignment, data:genome:fasta  genome, data:masterfile:amplicon  intervals, data:bed  intervals_bed, data:variants:vcf  dbsnp, basic:integer  stand_call_conf, basic:integer  stand_emit_conf, basic:integer  mbq)[Source: v0.4.0]

GATK HaplotypeCaller Variant Calling

Input arguments

alignment
label:Alignment file (BAM)
type:data:alignment:bam
genome
label:Genome
type:data:genome:fasta
intervals
label:Intervals (from master file)
type:data:masterfile:amplicon
description:Use this option to perform the analysis over only part of the genome. This option is not compatible with ``intervals_bed`` option.
required:False
intervals_bed
label:Intervals (from BED file)
type:data:bed
description:Use this option to perform the analysis over only part of the genome. This options is not compatible with ``intervals`` option.
required:False
dbsnp
label:dbSNP file
type:data:variants:vcf
stand_call_conf
label:Min call confidence threshold
type:basic:integer
description: The minimum phred-scaled confidence threshold at which variants should be called.
default:20
stand_emit_conf
label:Emission confidence threshold
type:basic:integer
description:The minimum confidence threshold (phred-scaled) at which the program should emit sites that appear to be possibly variant.
default:20
mbq
label:Min Base Quality
type:basic:integer
description:Minimum base quality required to consider a base for calling.
default:20

Output results

vcf
label:Variants
type:basic:file
tbi
label:Tabix index
type:basic:file
species
label:Species
type:basic:string
build
label:Build
type:basic:string
GATK4 (HaplotypeCaller)
data:variants:vcf:gatk:hcvc-gatk4-hc (data:alignment:bam  alignment, data:genome:fasta  genome, data:masterfile:amplicon  intervals, data:bed  intervals_bed, data:variants:vcf  dbsnp, basic:integer  stand_call_conf, basic:integer  mbq, basic:integer  max_reads)[Source: v0.2.0]

GATK HaplotypeCaller Variant Calling

Input arguments

alignment
label:Alignment file (BAM)
type:data:alignment:bam
genome
label:Genome
type:data:genome:fasta
intervals
label:Intervals (from master file)
type:data:masterfile:amplicon
description:Use this option to perform the analysis over only part of the genome. This option is not compatible with ``intervals_bed`` option.
required:False
intervals_bed
label:Intervals (from BED file)
type:data:bed
description:Use this option to perform the analysis over only part of the genome. This options is not compatible with ``intervals`` option.
required:False
dbsnp
label:dbSNP file
type:data:variants:vcf
stand_call_conf
label:Min call confidence threshold
type:basic:integer
description:The minimum phred-scaled confidence threshold at which variants should be called.
default:20
mbq
label:Min Base Quality
type:basic:integer
description:Minimum base quality required to consider a base for calling.
default:20
max_reads
label:Max reads per aligment start site
type:basic:integer
description:Maximum number of reads to retain per alignment start position. Reads above this threshold will be downsampled. Set to 0 to disable.
default:50

Output results

vcf
label:Variants
type:basic:file
tbi
label:Tabix index
type:basic:file
species
label:Species
type:basic:string
build
label:Build
type:basic:string
GFF3 file
data:annotation:gff3upload-gff3 (basic:file  src, basic:string  source, basic:string  species, basic:string  build)[Source: v3.2.1]

Import a General Feature Format (GFF) file which is a file format used for describing genes and other features of DNA, RNA and protein sequences. See [here](https://useast.ensembl.org/info/website/upload/gff3.html) and [here](https://en.wikipedia.org/wiki/General_feature_format) for more information.

Input arguments

src
label:Annotation (GFF3)
type:basic:file
description:Annotation in GFF3 format. Supported extensions are: .gff, .gff3 and .gtf
validate_regex:\.(gff|gff3|gtf)(|\.gz|\.bz2|\.tgz|\.tar\.gz|\.tar\.bz2|\.zip|\.rar|\.7z)$
source
label:Gene ID database
type:basic:string
choices:
  • AFFY: AFFY
  • DICTYBASE: DICTYBASE
  • ENSEMBL: ENSEMBL
  • NCBI: NCBI
  • UCSC: UCSC
species
label:Species
type:basic:string
description:Species latin name.
choices:
  • Homo sapiens: Homo sapiens
  • Mus musculus: Mus musculus
  • Rattus norvegicus: Rattus norvegicus
  • Dictyostelium discoideum: Dictyostelium discoideum
  • Odocoileus virginianus texanus: Odocoileus virginianus texanus
  • Solanum tuberosum: Solanum tuberosum
build
label:Build
type:basic:string

Output results

annot
label:Uploaded GFF3 file
type:basic:file
annot_sorted
label:Sorted GFF3 file
type:basic:file
annot_sorted_idx_igv
label:IGV index for sorted GFF3
type:basic:file
annot_sorted_track_jbrowse
label:Jbrowse track for sorted GFF3
type:basic:file
source
label:Gene ID database
type:basic:string
species
label:Species
type:basic:string
build
label:Build
type:basic:string
GO Enrichment analysis
data:goeagoenrichment (data:ontology:obo  ontology, data:gaf  gaf, list:basic:string  genes, basic:string  source, basic:string  species, basic:decimal  pval_threshold, basic:integer  min_genes)[Source: v3.2.1]

Identify significantly enriched Gene Ontology terms for given genes.

Input arguments

ontology
label:Gene Ontology
type:data:ontology:obo
gaf
label:GO annotation file (GAF v2.0)
type:data:gaf
genes
label:List of genes
type:list:basic:string
placeholder:new gene id
source
label:Source
type:basic:string
species
label:Species
type:basic:string
description:Species latin name. This field is required if gene subset is set.
choices:
  • Homo sapiens: Homo sapiens
  • Mus musculus: Mus musculus
  • Rattus norvegicus: Rattus norvegicus
  • Dictyostelium discoideum: Dictyostelium discoideum
  • Odocoileus virginianus texanus: Odocoileus virginianus texanus
  • Solanum tuberosum: Solanum tuberosum
pval_threshold
label:P-value threshold
type:basic:decimal
required:False
default:0.1
min_genes
label:Minimum number of genes
type:basic:integer
description:Minimum number of genes on a GO term.
required:False
default:1

Output results

terms
label:Enriched terms
type:basic:json
source
label:Source
type:basic:string
species
label:Species
type:basic:string
GTF file
data:annotation:gtfupload-gtf (basic:file  src, basic:string  source, basic:string  species, basic:string  build)[Source: v3.2.1]

Import a Gene Transfer Format (GTF) file. It is a file format used to hold information about gene structure. It is a tab-delimited text format based on the general feature format (GFF), but contains some additional conventions specific to gene information. See [here](https://en.wikipedia.org/wiki/General_feature_format) for differences between GFF and GTF files.

Input arguments

src
label:Annotation (GTF)
type:basic:file
description:Annotation in GTF format.
validate_regex:\.(gtf|gff)(|\.gz|\.bz2|\.tgz|\.tar\.gz|\.tar\.bz2|\.zip|\.rar|\.7z)$
source
label:Gene ID database
type:basic:string
choices:
  • AFFY: AFFY
  • DICTYBASE: DICTYBASE
  • ENSEMBL: ENSEMBL
  • NCBI: NCBI
  • UCSC: UCSC
species
label:Species
type:basic:string
description:Species latin name.
choices:
  • Homo sapiens: Homo sapiens
  • Mus musculus: Mus musculus
  • Rattus norvegicus: Rattus norvegicus
  • Dictyostelium discoideum: Dictyostelium discoideum
  • Odocoileus virginianus texanus: Odocoileus virginianus texanus
  • Solanum tuberosum: Solanum tuberosum
build
label:Build
type:basic:string

Output results

annot
label:Uploaded GTF file
type:basic:file
annot_sorted
label:Sorted GTF file
type:basic:file
annot_sorted_idx_igv
label:IGV index for sorted GTF file
type:basic:file
required:False
annot_sorted_track_jbrowse
label:Jbrowse track for sorted GTF
type:basic:file
required:False
source
label:Gene ID database
type:basic:string
species
label:Species
type:basic:string
build
label:Build
type:basic:string
Gene expression indices
data:index:expressionindex-fasta-nucl (data:seq:nucleotide  nucl, basic:string  nucl_genome, data:genome:fasta  genome, data:annotation:gtf  annotation, basic:string  source, basic:string  species, basic:string  build)[Source: v0.3.2]

Generate gene expression indices.

Input arguments

nucl
label:Nucleotide sequence
type:data:seq:nucleotide
required:False
hidden:genome
nucl_genome
label:Type of nucleotide sequence
type:basic:string
hidden:!nucl
default:gs
choices:
  • Genome sequence: gs
  • Transcript sequences: ts
genome
label:Genome sequence
type:data:genome:fasta
required:False
hidden:nucl
annotation
label:Annotation
type:data:annotation:gtf
required:False
hidden:nucl && nucl_genome == ‘ts’
source
label:Gene ID database
type:basic:string
required:False
hidden:!(nucl && nucl_genome == ‘ts’)
choices:
  • AFFY: AFFY
  • DICTYBASE: DICTYBASE
  • ENSEMBL: ENSEMBL
  • NCBI: NCBI
  • UCSC: UCSC
species
label:Species
type:basic:string
description:Species latin name.
required:False
hidden:!(nucl && nucl_genome == ‘ts’)
choices:
  • Homo sapiens: Homo sapiens
  • Mus musculus: Mus musculus
  • Rattus norvegicus: Rattus norvegicus
  • Dictyostelium discoideum: Dictyostelium discoideum
  • Odocoileus virginianus texanus: Odocoileus virginianus texanus
  • Solanum tuberosum: Solanum tuberosum
build
label:Genome build
type:basic:string
required:False
hidden:!(nucl && nucl_genome == ‘ts’)

Output results

rsem_index
label:RSEM index
type:basic:dir
source
label:Gene ID database
type:basic:string
species
label:Species
type:basic:string
build
label:Build
type:basic:string
Gene set
data:genesetupload-geneset (basic:file  src, basic:string  source, basic:string  species)[Source: v1.1.2]

Import a set of genes. Provide one gene ID per line in a .tab, .tab.gz, or .txt file format.

Input arguments

src
label:Gene set
type:basic:file
description:List of genes (.tab/.txt, one Gene ID per line. Supported extensions: .tab, .tab.gz (preferred), tab.*
validate_regex:(\.(tab|txt)(|\.gz|\.bz2|\.tgz|\.tar\.gz|\.tar\.bz2|\.zip|\.rar|\.7z))|(\.bz2)$
source
label:Gene ID source
type:basic:string
choices:
  • AFFY: AFFY
  • DICTYBASE: DICTYBASE
  • ENSEMBL: ENSEMBL
  • NCBI: NCBI
  • UCSC: UCSC
species
label:Species
type:basic:string
description:Species latin name.
choices:
  • Homo sapiens: Homo sapiens
  • Mus musculus: Mus musculus
  • Rattus norvegicus: Rattus norvegicus
  • Dictyostelium discoideum: Dictyostelium discoideum
  • Odocoileus virginianus texanus: Odocoileus virginianus texanus
  • Solanum tuberosum: Solanum tuberosum

Output results

geneset
label:Gene set
type:basic:file
geneset_json
label:Gene set (JSON)
type:basic:json
source
label:Gene ID source
type:basic:string
species
label:Species
type:basic:string
Gene set (create from Venn diagram)
data:geneset:venncreate-geneset-venn (list:basic:string  genes, basic:string  source, basic:string  species, basic:file  venn)[Source: v1.1.2]

Create a gene set from a Venn diagram.

Input arguments

genes
label:Genes
type:list:basic:string
description:List of genes.
source
label:Gene ID source
type:basic:string
choices:
  • AFFY: AFFY
  • DICTYBASE: DICTYBASE
  • ENSEMBL: ENSEMBL
  • NCBI: NCBI
  • UCSC: UCSC
species
label:Species
type:basic:string
description:Species latin name.
choices:
  • Homo sapiens: Homo sapiens
  • Mus musculus: Mus musculus
  • Rattus norvegicus: Rattus norvegicus
  • Dictyostelium discoideum: Dictyostelium discoideum
  • Odocoileus virginianus texanus: Odocoileus virginianus texanus
  • Solanum tuberosum: Solanum tuberosum
venn
label:Venn diagram
type:basic:file
description:JSON file. Supported extensions: .json.gz
validate_regex:(\.json)(|\.gz|\.bz2|\.tgz|\.tar\.gz|\.tar\.bz2|\.zip|\.rar|\.7z)$

Output results

geneset
label:Gene set
type:basic:file
geneset_json
label:Gene set (JSON)
type:basic:json
source
label:Gene ID source
type:basic:string
species
label:Species
type:basic:string
venn
label:Venn diagram
type:basic:json
Gene set (create)
data:genesetcreate-geneset (list:basic:string  genes, basic:string  source, basic:string  species)[Source: v1.1.2]

Create a gene set from a list of genes.

Input arguments

genes
label:Genes
type:list:basic:string
description:List of genes.
source
label:Gene ID source
type:basic:string
choices:
  • AFFY: AFFY
  • DICTYBASE: DICTYBASE
  • ENSEMBL: ENSEMBL
  • NCBI: NCBI
  • UCSC: UCSC
species
label:Species
type:basic:string
description:Species latin name.
choices:
  • Homo sapiens: Homo sapiens
  • Mus musculus: Mus musculus
  • Rattus norvegicus: Rattus norvegicus
  • Dictyostelium discoideum: Dictyostelium discoideum
  • Odocoileus virginianus texanus: Odocoileus virginianus texanus
  • Solanum tuberosum: Solanum tuberosum

Output results

geneset
label:Gene set
type:basic:file
geneset_json
label:Gene set (JSON)
type:basic:json
source
label:Gene ID source
type:basic:string
species
label:Species
type:basic:string
Genome
data:genome:fastaupload-genome (basic:file  src, basic:string  species, basic:string  build, basic:file  bowtie_index, basic:file  bowtie2_index, basic:file  bwa_index, basic:file  hisat2_index, basic:file  subread_index, basic:file  walt_index)[Source: v3.3.2]

Import genome sequence in FASTA format which includes .fasta.gz (preferred), .fa., .fna., or .fasta extensions.

Input arguments

src
label:Genome sequence (FASTA)
type:basic:file
description:Genome sequence in FASTA format. Supported extensions: .fasta.gz (preferred), .fa.*, .fna.* or .fasta.*
validate_regex:\.(fasta|fa|fna|fsa)(|\.gz|\.bz2|\.tgz|\.tar\.gz|\.tar\.bz2|\.zip|\.rar|\.7z)$
species
label:Species
type:basic:string
description:Species latin name.
choices:
  • Homo sapiens: Homo sapiens
  • Mus musculus: Mus musculus
  • Rattus norvegicus: Rattus norvegicus
  • Dictyostelium discoideum: Dictyostelium discoideum
  • Odocoileus virginianus texanus: Odocoileus virginianus texanus
  • Solanum tuberosum: Solanum tuberosum
build
label:Genome build
type:basic:string
advanced.bowtie_index
label:Bowtie index files
type:basic:file
description:Bowtie index files. Supported extensions (*.tar.gz).
required:False
validate_regex:(\.tar\.gz)$
advanced.bowtie2_index
label:Bowtie2 index files
type:basic:file
description:Bowtie2 index files. Supported extensions (*.tar.gz).
required:False
validate_regex:(\.tar\.gz)$
advanced.bwa_index
label:BWA index files
type:basic:file
description:BWA index files. Supported extensions (*.tar.gz).
required:False
validate_regex:(\.tar\.gz)$
advanced.hisat2_index
label:HISAT2 index files
type:basic:file
description:HISAT2 index files. Supported extensions (*.tar.gz).
required:False
validate_regex:(\.tar\.gz)$
advanced.subread_index
label:subread index files
type:basic:file
description:Subread index files. Supported extensions (*.tar.gz).
required:False
validate_regex:(\.tar\.gz)$
advanced.walt_index
label:WALT index files
type:basic:file
description:WALT index files. Supported extensions (*.tar.gz).
required:False
validate_regex:(\.tar\.gz)$

Output results

fastagz
label:Genome FASTA file (compressed)
type:basic:file
fasta
label:Genome FASTA file
type:basic:file
index_bt
label:Bowtie index
type:basic:dir
index_bt2
label:Bowtie2 index
type:basic:dir
index_bwa
label:BWA index
type:basic:dir
index_hisat2
label:HISAT2 index
type:basic:dir
index_subread
label:subread index
type:basic:dir
index_walt
label:WALT index
type:basic:dir
fai
label:Fasta index
type:basic:file
dict
label:Fasta dict
type:basic:file
fasta_track_jbrowse
label:Jbrowse track
type:basic:file
hidden:True
species
label:Species
type:basic:string
build
label:Build
type:basic:string
HISAT2
data:alignment:bam:hisat2alignment-hisat2 (data:genome:fasta  genome, data:reads:fastq  reads, basic:boolean  softclip, basic:integer  noncansplice, basic:boolean  cufflinks)[Source: v1.6.1]

HISAT2 is a fast and sensitive alignment program for mapping next-generation sequencing reads (both DNA and RNA) to a population of genomes (as well as to a single reference genome). See [here](https://ccb.jhu.edu/software/hisat2/index.shtml) for more information.

Input arguments

genome
label:Reference genome
type:data:genome:fasta
reads
label:Reads
type:data:reads:fastq
softclip
label:Disallow soft clipping
type:basic:boolean
default:False
spliced_alignments.noncansplice
label:Non-canonical splice sites penalty (optional)
type:basic:integer
description:Sets the penalty for each pair of non-canonical splice sites (e.g. non-GT/AG).
required:False
spliced_alignments.cufflinks
label:Report alignments tailored specifically for Cufflinks
type:basic:boolean
description:With this option, HISAT2 looks for novel splice sites with three signals (GT/AG, GC/AG, AT/AC), but all user-provided splice sites are used irrespective of their signals. HISAT2 produces an optional field, XS:A:[+-], for every spliced alignment.
default:False

Output results

bam
label:Alignment file
type:basic:file
description:Position sorted alignment
bai
label:Index BAI
type:basic:file
stats
label:Statistics
type:basic:file
splice_junctions
label:Splice junctions
type:basic:file
unmapped_f
label:Unmapped reads (mate 1)
type:basic:file
required:False
unmapped_r
label:Unmapped reads (mate 2)
type:basic:file
required:False
bigwig
label:BigWig file
type:basic:file
required:False
species
label:Species
type:basic:string
build
label:Build
type:basic:string
HMR
data:wgbs:hmrhmr (data:wgbs:methcounts  methcounts)[Source: v1.1.0]

Identify hypo-methylated regions.

Input arguments

methcounts
label:Methylation levels
type:data:wgbs:methcounts
description:Methylation levels data calculated using methcounts.

Output results

hmr
label:Hypo-methylated regions
type:basic:file
tbi_jbrowse
label:Bed file index for Jbrowse
type:basic:file
species
label:Species
type:basic:string
build
label:Build
type:basic:string
HTSeq-count (CPM)
data:expression:htseq:cpmhtseq-count-raw (data:alignment:bam  alignments, data:annotation:gtf  gtf, basic:string  mode, basic:string  stranded, basic:string  feature_class, basic:string  id_attribute, basic:string  feature_type, basic:boolean  name_ordered)[Source: v1.5.1]

HTSeq-count is useful for preprocessing RNA-Seq alignments for differential expression calling. It counts the number of reads that map to a genomic feature (e.g. gene). For computationally efficient quantification consider using featureCounts instead of HTSeq-count. The expressions with raw counts, produced by HTSeq are then normalized by computing CPM. See [the official website](https://htseq.readthedocs.io/en/release_0.9.1) and [the introductory paper](https://academic.oup.com/bioinformatics/article/31/2/166/2366196) for more information. For computationally efficient quantification consider using featureCounts instead of HTSeq-count.

Input arguments

alignments
label:Aligned reads
type:data:alignment:bam
gtf
label:Annotation (GTF)
type:data:annotation:gtf
mode
label:Mode
type:basic:string
description:Mode to handle reads overlapping more than one feature. Possible values for <mode> are union, intersection-strict and intersection-nonempty
default:union
choices:
  • union: union
  • intersection-strict: intersection-strict
  • intersection-nonempty: intersection-nonempty
stranded
label:Is data from a strand specific assay?
type:basic:string
description:For stranded=no, a read is considered overlapping with a feature regardless of whether it is mapped to the same or the opposite strand as the feature. For stranded=yes and single-end reads, the read has to be mapped to the same strand as the feature. For paired-end reads, the first read has to be on the same strand and the second read on the opposite strand. For stranded=reverse, these rules are reversed
default:yes
choices:
  • yes: yes
  • no: no
  • reverse: reverse
feature_class
label:Feature class
type:basic:string
description:Feature class (3rd column in GTF file) to be used. All other features will be ignored.
default:exon
id_attribute
label:ID attribute
type:basic:string
description:GFF attribute to be used as feature ID. Several GTF lines with the same feature ID will be considered as parts of the same feature. The feature ID is used to identity the counts in the output table.
default:gene_id
feature_type
label:Feature type
type:basic:string
description:The type of feature the quantification program summarizes over (e.g. gene or transcript-level analysis).
default:gene
choices:
  • gene: gene
  • transcript: transcript
name_ordered
label:Use name-ordered BAM file for counting reads
type:basic:boolean
description:Use name-sorted BAM file for reads quantification. Improves compatibility with larger BAM files, but requires more computational time. Setting this to false may cause the process to fail for large BAM files due to buffer overflow.
default:True

Output results

htseq_output
label:HTseq-count output
type:basic:file
rc
label:Read count
type:basic:file
exp
label:CPM (Counts per million)
type:basic:file
exp_json
label:CPM (json)
type:basic:json
exp_set
label:Expressions
type:basic:file
exp_set_json
label:Expressions (json)
type:basic:json
exp_type
label:Expression Type (default output)
type:basic:string
source
label:Gene ID database
type:basic:string
species
label:Species
type:basic:string
build
label:Build
type:basic:string
feature_type
label:Feature type
type:basic:string
HTSeq-count (TPM)
data:expression:htseq:normalizedhtseq-count (data:alignment:bam  alignments, data:annotation:gtf  gff, basic:string  mode, basic:string  stranded, basic:string  feature_class, basic:string  id_attribute, basic:string  feature_type, basic:boolean  name_ordered)[Source: v1.4.1]

HTSeq-count is useful for preprocessing RNA-Seq alignments for differential expression calling. It counts the number of reads that map to a genomic feature (e.g. gene). The expressions with raw counts, produced by HTSeq are then normalized by computing FPKM and TPM. For computationally efficient quantification consider using featureCounts instead of HTSeq-count.

Input arguments

alignments
label:Aligned reads
type:data:alignment:bam
gff
label:Annotation (GFF)
type:data:annotation:gtf
mode
label:Mode
type:basic:string
description:Mode to handle reads overlapping more than one feature. Possible values for <mode> are union, intersection-strict and intersection-nonempty
default:union
choices:
  • union: union
  • intersection-strict: intersection-strict
  • intersection-nonempty: intersection-nonempty
stranded
label:Is data from a strand specific assay?
type:basic:string
description:For stranded=no, a read is considered overlapping with a feature regardless of whether it is mapped to the same or the opposite strand as the feature. For stranded=yes and single-end reads, the read has to be mapped to the same strand as the feature. For paired-end reads, the first read has to be on the same strand and the second read on the opposite strand. For stranded=reverse, these rules are reversed
default:yes
choices:
  • yes: yes
  • no: no
  • reverse: reverse
feature_class
label:Feature class
type:basic:string
description:Feature class (3rd column in GFF file) to be used. All other features will be ignored.
default:exon
id_attribute
label:ID attribute
type:basic:string
description:GFF attribute to be used as feature ID. Several GFF lines with the same feature ID will be considered as parts of the same feature. The feature ID is used to identity the counts in the output table.
default:gene_id
feature_type
label:Feature type
type:basic:string
description:The type of feature the quantification program summarizes over (e.g. gene or transcript-level analysis).
default:gene
choices:
  • gene: gene
  • transcript: transcript
name_ordered
label:Use name-ordered BAM file for counting reads
type:basic:boolean
description:Use name-sorted BAM file for reads quantification. Improves compatibility with larger BAM files, but requires more computational time. Setting this to false may cause the process to fail for large BAM files due to buffer overflow.
default:True

Output results

htseq_output
label:HTseq-count output
type:basic:file
rc
label:Read counts
type:basic:file
fpkm
label:FPKM
type:basic:file
exp
label:TPM (Transcripts Per Million)
type:basic:file
exp_json
label:TPM (json)
type:basic:json
exp_type
label:Expression Type (default output)
type:basic:string
exp_set
label:Expressions
type:basic:file
exp_set_json
label:Expressions (json)
type:basic:json
source
label:Gene ID database
type:basic:string
species
label:Species
type:basic:string
build
label:Build
type:basic:string
feature_type
label:Feature type
type:basic:string
Hierarchical clustering of genes
data:clustering:hierarchical:geneclustering-hierarchical-genes (list:data:expression  exps, basic:boolean  advanced, list:basic:string  genes, basic:string  source, basic:string  species, basic:boolean  log2, basic:boolean  z_score, basic:string  distance_metric, basic:string  linkage_method, basic:boolean  order)[Source: v3.0.1]

Hierarchical clustering of genes.

Input arguments

exps
label:Expressions
type:list:data:expression
description:Select at least two data objects.
advanced
label:Show advanced options
type:basic:boolean
default:False
preprocessing.genes
label:Gene subset
type:list:basic:string
description:Select at least two genes or leave this field empty.
required:False
placeholder:new gene id
preprocessing.source
label:Gene ID database of selected genes
type:basic:string
description:This field is required if gene subset is set.
required:False
hidden:!preprocessing.genes
preprocessing.species
label:Species
type:basic:string
description:Species latin name. This field is required if gene subset is set.
required:False
hidden:!preprocessing.genes
choices:
  • Homo sapiens: Homo sapiens
  • Mus musculus: Mus musculus
  • Rattus norvegicus: Rattus norvegicus
  • Dictyostelium discoideum: Dictyostelium discoideum
  • Odocoileus virginianus texanus: Odocoileus virginianus texanus
  • Solanum tuberosum: Solanum tuberosum
preprocessing.log2
label:Log-transform expressions
type:basic:boolean
description:Transform expressions with log2(x + 1) before clustering.
default:True
preprocessing.z_score
label:Z-score normalization
type:basic:boolean
description:Use Z-score normalization of gene expressions before clustering.
default:True
processing.distance_metric
label:Distance metric
type:basic:string
default:pearson
choices:
  • Euclidean: euclidean
  • Pearson: pearson
  • Spearman: spearman
processing.linkage_method
label:Linkage method
type:basic:string
default:average
choices:
  • single: single
  • average: average
  • complete: complete
postprocessing.order
label:Order samples optimally
type:basic:boolean
default:True

Output results

cluster
label:Hierarchical clustering
type:basic:json
required:False
Hierarchical clustering of samples
data:clustering:hierarchical:sampleclustering-hierarchical-samples (list:data:expression  exps, basic:boolean  advanced, list:basic:string  genes, basic:string  source, basic:string  species, basic:boolean  log2, basic:boolean  z_score, basic:string  distance_metric, basic:string  linkage_method, basic:boolean  order)[Source: v3.0.1]

Hierarchical clustering of samples.

Input arguments

exps
label:Expressions
type:list:data:expression
description:Select at least two data objects.
advanced
label:Show advanced options
type:basic:boolean
default:False
preprocessing.genes
label:Gene subset
type:list:basic:string
description:Select at least two genes or leave this field empty.
required:False
placeholder:new gene id
preprocessing.source
label:Gene ID database of selected genes
type:basic:string
description:This field is required if gene subset is set.
required:False
hidden:!preprocessing.genes
preprocessing.species
label:Species
type:basic:string
description:Species latin name. This field is required if gene subset is set.
required:False
hidden:!preprocessing.genes
choices:
  • Homo sapiens: Homo sapiens
  • Mus musculus: Mus musculus
  • Rattus norvegicus: Rattus norvegicus
  • Dictyostelium discoideum: Dictyostelium discoideum
  • Odocoileus virginianus texanus: Odocoileus virginianus texanus
  • Solanum tuberosum: Solanum tuberosum
preprocessing.log2
label:Log-transform expressions
type:basic:boolean
description:Transform expressions with log2(x + 1) before clustering.
default:True
preprocessing.z_score
label:Z-score normalization
type:basic:boolean
description:Use Z-score normalization of gene expressions before clustering.
default:True
processing.distance_metric
label:Distance metric
type:basic:string
default:pearson
choices:
  • Euclidean: euclidean
  • Pearson: pearson
  • Spearman: spearman
processing.linkage_method
label:Linkage method
type:basic:string
default:average
choices:
  • single: single
  • average: average
  • complete: complete
postprocessing.order
label:Order samples optimally
type:basic:boolean
default:True

Output results

cluster
label:Hierarchical clustering
type:basic:json
required:False
Indel Realignment and Base Recalibration
data:alignment:bam:vcvc-realign-recalibrate (data:alignment:bam  alignment, data:genome:fasta  genome, list:data:variants:vcf  known_vars, list:data:variants:vcf  known_indels)[Source: v1.0.2]

Preprocess BAM file and prepare for Variant Calling.

Input arguments

alignment
label:Alignment file (BAM)
type:data:alignment:bam
genome
label:Genome
type:data:genome:fasta
known_vars
label:Known sites (dbSNP)
type:list:data:variants:vcf
known_indels
label:Known indels
type:list:data:variants:vcf

Output results

bam
label:Alignment file
type:basic:file
bai
label:Index BAI
type:basic:file
stats
label:Stats
type:basic:file
species
label:Species
type:basic:string
build
label:Build
type:basic:string
LoFreq (call)
data:variants:vcf:lofreqlofreq (data:alignment:bam  alignment, data:genome:fasta  genome, data:masterfile:amplicon  intervals, basic:integer  min_bq, basic:integer  min_alt_bq)[Source: v0.4.1]

Lofreq (call) Variant Calling.

Input arguments

alignment
label:Alignment file (BAM)
type:data:alignment:bam
genome
label:Genome
type:data:genome:fasta
intervals
label:Intervals
type:data:masterfile:amplicon
description:Use this option to perform the analysis over only part of the genome.
min_bq
label:Min baseQ
type:basic:integer
description:Skip any base with baseQ smaller than the default value.
default:6
min_alt_bq
label:Min alternate baseQ
type:basic:integer
description:Skip alternate bases with baseQ smaller than the default value.
default:6

Output results

vcf
label:Variants
type:basic:file
tbi
label:Tabix index
type:basic:file
species
label:Species
type:basic:string
build
label:Build
type:basic:string
MACS 1.4
data:chipseq:callpeak:macs14macs14 (data:alignment:bam  treatment, data:alignment:bam  control, basic:string  pvalue)[Source: v3.2.1]

Model-based Analysis of ChIP-Seq (MACS 1.4) empirically models the length of the sequenced ChIP fragments, which tends to be shorter than sonication or library construction size estimates, and uses it to improve the spatial resolution of predicted binding sites. MACS also uses a dynamic Poisson distribution to effectively capture local biases in the genome sequence, allowing for more sensitive and robust prediction. See the [original paper](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2592715/) for more information.

Input arguments

treatment
label:BAM File
type:data:alignment:bam
control
label:BAM Background File
type:data:alignment:bam
required:False
pvalue
label:P-value
type:basic:string
default:1e-9
choices:
  • 1e-9: 1e-9
  • 1e-6: 1e-6

Output results

peaks_bed
label:Peaks (BED)
type:basic:file
summits_bed
label:Summits (BED)
type:basic:file
peaks_xls
label:Peaks (XLS)
type:basic:file
wiggle
label:Wiggle
type:basic:file
control_bigwig
label:Control (bigWig)
type:basic:file
required:False
treat_bigwig
label:Treat (bigWig)
type:basic:file
peaks_bigbed_igv_ucsc
label:Peaks (bigBed)
type:basic:file
required:False
summits_bigbed_igv_ucsc
label:Summits (bigBed)
type:basic:file
required:False
peaks_tbi_jbrowse
label:JBrowse track peaks file
type:basic:file
summits_tbi_jbrowse
label:JBrowse track summits file
type:basic:file
model
label:Model
type:basic:file
required:False
neg_peaks
label:Negative peaks (XLS)
type:basic:file
required:False
species
label:Species
type:basic:string
build
label:Build
type:basic:string
MACS 2.0
data:chipseq:callpeak:macs2macs2-callpeak (data:alignment:bam  case, data:alignment:bam  control, data:bed  promoter, basic:boolean  tagalign, basic:integer  q_threshold, basic:integer  n_sub, basic:boolean  tn5, basic:integer  shift, basic:string  duplicates, basic:string  duplicates_prepeak, basic:decimal  qvalue, basic:decimal  pvalue, basic:decimal  pvalue_prepeak, basic:integer  cap_num, basic:integer  mfold_lower, basic:integer  mfold_upper, basic:integer  slocal, basic:integer  llocal, basic:integer  extsize, basic:integer  shift, basic:integer  band_width, basic:boolean  nolambda, basic:boolean  fix_bimodal, basic:boolean  nomodel, basic:boolean  nomodel_prepeak, basic:boolean  down_sample, basic:boolean  bedgraph, basic:boolean  spmr, basic:boolean  call_summits, basic:boolean  broad, basic:decimal  broad_cutoff)[Source: v4.0.4]

Model-based Analysis of ChIP-Seq (MACS 2.0), is used to identify transcript factor binding sites. MACS 2.0 captures the influence of genome complexity to evaluate the significance of enriched ChIP regions, and MACS improves the spatial resolution of binding sites through combining the information of both sequencing tag position and orientation. It has also an option to link nearby peaks together in order to call broad peaks. See [here](https://github.com/taoliu/MACS/) for more information. In addition to peak-calling, this process computes ChIP-Seq and ATAC-Seq QC metrics. Process returns a QC metrics report, fragment length estimation, and a deduplicated tagAlign file. QC report contains ENCODE 3 proposed QC metrics – [NRF](https://www.encodeproject.org/data-standards/terms/), [PBC bottlenecking coefficients, NSC, and RSC](https://genome.ucsc.edu/ENCODE/qualityMetrics.html#chipSeq).

Input arguments

case
label:Case (treatment)
type:data:alignment:bam
control
label:Control (background)
type:data:alignment:bam
required:False
promoter
label:Promoter regions BED file
type:data:bed
description:BED file containing promoter regions (TSS+-1000bp for example). Needed to get the number of peaks and reads mapped to promoter regions.
required:False
tagalign
label:Use tagAlign files
type:basic:boolean
description:Use filtered tagAlign files as case (treatment) and control (background) samples. If extsize parameter is not set, run MACS using input’s estimated fragment length.
default:False
prepeakqc_settings.q_threshold
label:Quality filtering threshold
type:basic:integer
default:30
prepeakqc_settings.n_sub
label:Number of reads to subsample
type:basic:integer
default:15000000
prepeakqc_settings.tn5
label:TN5 shifting
type:basic:boolean
description:Tn5 transposon shifting. Shift reads on “+” strand by 4bp and reads on “-” strand by 5bp.
default:False
prepeakqc_settings.shift
label:User-defined cross-correlation peak strandshift
type:basic:integer
description:If defined, SPP tool will not try to estimate fragment length but will use the given value as fragment length.
required:False
settings.duplicates
label:Number of duplicates
type:basic:string
description:It controls the MACS behavior towards duplicate tags at the exact same location – the same coordination and the same strand. The ‘auto’ option makes MACS calculate the maximum tags at the exact same location based on binomal distribution using 1e-5 as pvalue cutoff and the ‘all’ option keeps all the tags. If an integer is given, at most this number of tags will be kept at the same location. The default is to keep one tag at the same location.
required:False
hidden:tagalign
choices:
  • 1: 1
  • auto: auto
  • all: all
settings.duplicates_prepeak
label:Number of duplicates
type:basic:string
description:It controls the MACS behavior towards duplicate tags at the exact same location – the same coordination and the same strand. The ‘auto’ option makes MACS calculate the maximum tags at the exact same location based on binomal distribution using 1e-5 as pvalue cutoff and the ‘all’ option keeps all the tags. If an integer is given, at most this number of tags will be kept at the same location. The default is to keep one tag at the same location.
required:False
hidden:!tagalign
default:all
choices:
  • 1: 1
  • auto: auto
  • all: all
settings.qvalue
label:Q-value cutoff
type:basic:decimal
description:The q-value (minimum FDR) cutoff to call significant regions. Q-values are calculated from p-values using Benjamini-Hochberg procedure.
required:False
disabled:settings.pvalue && settings.pvalue_prepeak
settings.pvalue
label:P-value cutoff
type:basic:decimal
description:The p-value cutoff. If specified, MACS2 will use p-value instead of q-value cutoff.
required:False
disabled:settings.qvalue
hidden:tagalign
settings.pvalue_prepeak
label:P-value cutoff
type:basic:decimal
description:The p-value cutoff. If specified, MACS2 will use p-value instead of q-value cutoff.
disabled:settings.qvalue
hidden:!tagalign || settings.qvalue
default:1e-05
settings.cap_num
label:Cap number of peaks by taking top N peaks
type:basic:integer
description:To keep all peaks set value to 0.
disabled:settings.broad
default:500000
settings.mfold_lower
label:MFOLD range (lower limit)
type:basic:integer
description:This parameter is used to select the regions within MFOLD range of high-confidence enrichment ratio against background to build model. The regions must be lower than upper limit, and higher than the lower limit of fold enrichment. DEFAULT:10,30 means using all regions not too low (>10) and not too high (<30) to build paired-peaks model. If MACS can not find more than 100 regions to build model, it will use the –extsize parameter to continue the peak detection ONLY if –fix-bimodal is set.
required:False
settings.mfold_upper
label:MFOLD range (upper limit)
type:basic:integer
description:This parameter is used to select the regions within MFOLD range of high-confidence enrichment ratio against background to build model. The regions must be lower than upper limit, and higher than the lower limit of fold enrichment. DEFAULT:10,30 means using all regions not too low (>10) and not too high (<30) to build paired-peaks model. If MACS can not find more than 100 regions to build model, it will use the –extsize parameter to continue the peak detection ONLY if –fix-bimodal is set.
required:False
settings.slocal
label:Small local region
type:basic:integer
description:Slocal and llocal parameters control which two levels of regions will be checked around the peak regions to calculate the maximum lambda as local lambda. By default, MACS considers 1000bp for small local region (–slocal), and 10000bps for large local region (–llocal) which captures the bias from a long range effect like an open chromatin domain. You can tweak these according to your project. Remember that if the region is set too small, a sharp spike in the input data may kill the significant peak.
required:False
settings.llocal
label:Large local region
type:basic:integer
description:Slocal and llocal parameters control which two levels of regions will be checked around the peak regions to calculate the maximum lambda as local lambda. By default, MACS considers 1000bp for small local region (–slocal), and 10000bps for large local region (–llocal) which captures the bias from a long range effect like an open chromatin domain. You can tweak these according to your project. Remember that if the region is set too small, a sharp spike in the input data may kill the significant peak.
required:False
settings.extsize
label:extsize
type:basic:integer
description:While ‘–nomodel’ is set, MACS uses this parameter to extend reads in 5’->3’ direction to fix-sized fragments. For example, if the size of binding region for your transcription factor is 200 bp, and you want to bypass the model building by MACS, this parameter can be set as 200. This option is only valid when –nomodel is set or when MACS fails to build model and –fix-bimodal is on.
required:False
settings.shift
label:Shift
type:basic:integer
description:Note, this is NOT the legacy –shiftsize option which is replaced by –extsize! You can set an arbitrary shift in bp here. Please Use discretion while setting it other than default value (0). When –nomodel is set, MACS will use this value to move cutting ends (5’) then apply –extsize from 5’ to 3’ direction to extend them to fragments. When this value is negative, ends will be moved toward 3’->5’ direction, otherwise 5’->3’ direction. Recommended to keep it as default 0 for ChIP-Seq datasets, or -1 * half of EXTSIZE together with –extsize option for detecting enriched cutting loci such as certain DNAseI-Seq datasets. Note, you can’t set values other than 0 if format is BAMPE for paired-end data. Default is 0.
required:False
settings.band_width
label:Band width
type:basic:integer
description:The band width which is used to scan the genome ONLY for model building. You can set this parameter as the sonication fragment size expected from wet experiment. The previous side effect on the peak detection process has been removed. So this parameter only affects the model building.
required:False
settings.nolambda
label:Use backgroud lambda as local lambda
type:basic:boolean
description:With this flag on, MACS will use the background lambda as local lambda. This means MACS will not consider the local bias at peak candidate regions.
default:False
settings.fix_bimodal
label:Turn on the auto paired-peak model process
type:basic:boolean
description:Whether turn on the auto paired-peak model process. If it’s set, when MACS failed to build paired model, it will use the nomodel settings, the ‘–extsize’ parameter to extend each tags. If set, MACS will be terminated if paired-peak model is failed.
default:False
settings.nomodel
label:Bypass building the shifting model
type:basic:boolean
description:While on, MACS will bypass building the shifting model.
hidden:tagalign
default:False
settings.nomodel_prepeak
label:Bypass building the shifting model
type:basic:boolean
description:While on, MACS will bypass building the shifting model.
hidden:!tagalign
default:True
settings.down_sample
label:Down-sample
type:basic:boolean
description:When set, random sampling method will scale down the bigger sample. By default, MACS uses linear scaling. This option will make the results unstable and irreproducible since each time, random reads would be selected, especially the numbers (pileup, pvalue, qvalue) would change. Consider to use ‘randsample’ script before MACS2 runs instead.
default:False
settings.bedgraph
label:Save fragment pileup and control lambda
type:basic:boolean
description:If this flag is on, MACS will store the fragment pileup, control lambda, -log10pvalue and -log10qvalue scores in bedGraph files. The bedGraph files will be stored in current directory named NAME+’_treat_pileup.bdg’ for treatment data, NAME+’_control_lambda.bdg’ for local lambda values from control, NAME+’_treat_pvalue.bdg’ for Poisson pvalue scores (in -log10(pvalue) form), and NAME+’_treat_qvalue.bdg’ for q-value scores from Benjamini-Hochberg-Yekutieli procedure.
default:True
settings.spmr
label:Save signal per million reads for fragment pileup profiles
type:basic:boolean
disabled:settings.bedgraph === false
default:True
settings.call_summits
label:Call summits
type:basic:boolean
description:MACS will now reanalyze the shape of signal profile (p or q-score depending on cutoff setting) to deconvolve subpeaks within each peak called from general procedure. It’s highly recommended to detect adjacent binding events. While used, the output subpeaks of a big peak region will have the same peak boundaries, and different scores and peak summit positions.
default:False
settings.broad
label:Composite broad regions
type:basic:boolean
description:When this flag is on, MACS will try to composite broad regions in BED12 (a gene-model-like format) by putting nearby highly enriched regions into a broad region with loose cutoff. The broad region is controlled by another cutoff through –broad-cutoff. The maximum length of broad region length is 4 times of d from MACS.
disabled:settings.call_summits === true
default:False
settings.broad_cutoff
label:Broad cutoff
type:basic:decimal
description:Cutoff for broad region. This option is not available unless –broad is set. If -p is set, this is a p-value cutoff, otherwise, it’s a q-value cutoff. DEFAULT = 0.1
required:False
disabled:settings.call_summits === true || settings.broad !== true

Output results

called_peaks
label:Called peaks
type:basic:file
narrow_peaks
label:Narrow peaks
type:basic:file
required:False
chip_qc
label:QC report
type:basic:file
required:False
case_prepeak_qc
label:Pre-peak QC report (case)
type:basic:file
case_tagalign
label:Filtered tagAlign (case)
type:basic:file
control_prepeak_qc
label:Pre-peak QC report (control)
type:basic:file
required:False
control_tagalign
label:Filtered tagAlign (control)
type:basic:file
required:False
narrow_peaks_bigbed_igv_ucsc
label:Narrow peaks (BigBed)
type:basic:file
required:False
summits
label:Peak summits
type:basic:file
required:False
summits_tbi_jbrowse
label:Peak summits tbi index for JBrowse
type:basic:file
required:False
summits_bigbed_igv_ucsc
label:Summits (bigBed)
type:basic:file
required:False
broad_peaks
label:Broad peaks
type:basic:file
required:False
gappedPeak
label:Broad peaks (bed12/gappedPeak)
type:basic:file
required:False
treat_pileup
label:Treatment pileup (bedGraph)
type:basic:file
required:False
treat_pileup_bigwig
label:Treatment pileup (bigWig)
type:basic:file
required:False
control_lambda
label:Control lambda (bedGraph)
type:basic:file
required:False
control_lambda_bigwig
label:Control lambda (bigwig)
type:basic:file
required:False
model
label:Model
type:basic:file
required:False
species
label:Species
type:basic:string
build
label:Build
type:basic:string
MACS2 - ROSE2
data:workflow:chipseq:macs2rose2workflow-macs-rose (data:alignment:bam  case, data:alignment:bam  control, data:bed  promoter, basic:boolean  tagalign, basic:integer  q_threshold, basic:integer  n_sub, basic:boolean  tn5, basic:integer  shift, basic:string  duplicates, basic:string  duplicates_prepeak, basic:decimal  qvalue, basic:decimal  pvalue, basic:decimal  pvalue_prepeak, basic:integer  cap_num, basic:integer  mfold_lower, basic:integer  mfold_upper, basic:integer  slocal, basic:integer  llocal, basic:integer  extsize, basic:integer  shift, basic:integer  band_width, basic:boolean  nolambda, basic:boolean  fix_bimodal, basic:boolean  nomodel, basic:boolean  nomodel_prepeak, basic:boolean  down_sample, basic:boolean  bedgraph, basic:boolean  spmr, basic:boolean  call_summits, basic:boolean  broad, basic:decimal  broad_cutoff, basic:integer  tss, basic:integer  stitch, data:bed  mask)[Source: v1.0.1]

Input arguments

case
label:Case (treatment)
type:data:alignment:bam
control
label:Control (background)
type:data:alignment:bam
required:False
promoter
label:Promoter regions BED file
type:data:bed
description:BED file containing promoter regions (TSS+-1000bp for example). Needed to get the number of peaks and reads mapped to promoter regions.
required:False
tagalign
label:Use tagAlign files
type:basic:boolean
description:Use filtered tagAlign files as case (treatment) and control (background) samples. If extsize parameter is not set, run MACS using input’s estimated fragment length.
default:False
prepeakqc_settings.q_threshold
label:Quality filtering threshold
type:basic:integer
default:30
prepeakqc_settings.n_sub
label:Number of reads to subsample
type:basic:integer
default:15000000
prepeakqc_settings.tn5
label:TN5 shifting
type:basic:boolean
description:Tn5 transposon shifting. Shift reads on “+” strand by 4bp and reads on “-” strand by 5bp.
default:False
prepeakqc_settings.shift
label:User-defined cross-correlation peak strandshift
type:basic:integer
description:If defined, SPP tool will not try to estimate fragment length but will use the given value as fragment length.
required:False
settings.duplicates
label:Number of duplicates
type:basic:string
description:It controls the MACS behavior towards duplicate tags at the exact same location – the same coordination and the same strand. The ‘auto’ option makes MACS calculate the maximum tags at the exact same location based on binomal distribution using 1e-5 as pvalue cutoff and the ‘all’ option keeps all the tags. If an integer is given, at most this number of tags will be kept at the same location. The default is to keep one tag at the same location.
required:False
hidden:tagalign
choices:
  • 1: 1
  • auto: auto
  • all: all
settings.duplicates_prepeak
label:Number of duplicates
type:basic:string
description:It controls the MACS behavior towards duplicate tags at the exact same location – the same coordination and the same strand. The ‘auto’ option makes MACS calculate the maximum tags at the exact same location based on binomal distribution using 1e-5 as pvalue cutoff and the ‘all’ option keeps all the tags. If an integer is given, at most this number of tags will be kept at the same location. The default is to keep one tag at the same location.
required:False
hidden:!tagalign
default:all
choices:
  • 1: 1
  • auto: auto
  • all: all
settings.qvalue
label:Q-value cutoff
type:basic:decimal
description:The q-value (minimum FDR) cutoff to call significant regions. Q-values are calculated from p-values using Benjamini-Hochberg procedure.
required:False
disabled:settings.pvalue && settings.pvalue_prepeak
settings.pvalue
label:P-value cutoff
type:basic:decimal
description:The p-value cutoff. If specified, MACS2 will use p-value instead of q-value cutoff.
required:False
disabled:settings.qvalue
hidden:tagalign
settings.pvalue_prepeak
label:P-value cutoff
type:basic:decimal
description:The p-value cutoff. If specified, MACS2 will use p-value instead of q-value cutoff.
disabled:settings.qvalue
hidden:!tagalign || settings.qvalue
default:1e-05
settings.cap_num
label:Cap number of peaks by taking top N peaks
type:basic:integer
description:To keep all peaks set value to 0.
disabled:settings.broad
default:500000
settings.mfold_lower
label:MFOLD range (lower limit)
type:basic:integer
description:This parameter is used to select the regions within MFOLD range of high-confidence enrichment ratio against background to build model. The regions must be lower than upper limit, and higher than the lower limit of fold enrichment. DEFAULT:10,30 means using all regions not too low (>10) and not too high (<30) to build paired-peaks model. If MACS can not find more than 100 regions to build model, it will use the –extsize parameter to continue the peak detection ONLY if –fix-bimodal is set.
required:False
settings.mfold_upper
label:MFOLD range (upper limit)
type:basic:integer
description:This parameter is used to select the regions within MFOLD range of high-confidence enrichment ratio against background to build model. The regions must be lower than upper limit, and higher than the lower limit of fold enrichment. DEFAULT:10,30 means using all regions not too low (>10) and not too high (<30) to build paired-peaks model. If MACS can not find more than 100 regions to build model, it will use the –extsize parameter to continue the peak detection ONLY if –fix-bimodal is set.
required:False
settings.slocal
label:Small local region
type:basic:integer
description:Slocal and llocal parameters control which two levels of regions will be checked around the peak regions to calculate the maximum lambda as local lambda. By default, MACS considers 1000bp for small local region (–slocal), and 10000bps for large local region (–llocal) which captures the bias from a long range effect like an open chromatin domain. You can tweak these according to your project. Remember that if the region is set too small, a sharp spike in the input data may kill the significant peak.
required:False
settings.llocal
label:Large local region
type:basic:integer
description:Slocal and llocal parameters control which two levels of regions will be checked around the peak regions to calculate the maximum lambda as local lambda. By default, MACS considers 1000bp for small local region (–slocal), and 10000bps for large local region (–llocal) which captures the bias from a long range effect like an open chromatin domain. You can tweak these according to your project. Remember that if the region is set too small, a sharp spike in the input data may kill the significant peak.
required:False
settings.extsize
label:extsize
type:basic:integer
description:While ‘–nomodel’ is set, MACS uses this parameter to extend reads in 5’->3’ direction to fix-sized fragments. For example, if the size of binding region for your transcription factor is 200 bp, and you want to bypass the model building by MACS, this parameter can be set as 200. This option is only valid when –nomodel is set or when MACS fails to build model and –fix-bimodal is on.
required:False
settings.shift
label:Shift
type:basic:integer
description:Note, this is NOT the legacy –shiftsize option which is replaced by –extsize! You can set an arbitrary shift in bp here. Please Use discretion while setting it other than default value (0). When –nomodel is set, MACS will use this value to move cutting ends (5’) then apply –extsize from 5’ to 3’ direction to extend them to fragments. When this value is negative, ends will be moved toward 3’->5’ direction, otherwise 5’->3’ direction. Recommended to keep it as default 0 for ChIP-Seq datasets, or -1 * half of EXTSIZE together with –extsize option for detecting enriched cutting loci such as certain DNAseI-Seq datasets. Note, you can’t set values other than 0 if format is BAMPE for paired-end data. Default is 0.
required:False
settings.band_width
label:Band width
type:basic:integer
description:The band width which is used to scan the genome ONLY for model building. You can set this parameter as the sonication fragment size expected from wet experiment. The previous side effect on the peak detection process has been removed. So this parameter only affects the model building.
required:False
settings.nolambda
label:Use backgroud lambda as local lambda
type:basic:boolean
description:With this flag on, MACS will use the background lambda as local lambda. This means MACS will not consider the local bias at peak candidate regions.
default:False
settings.fix_bimodal
label:Turn on the auto paired-peak model process
type:basic:boolean
description:Whether turn on the auto paired-peak model process. If it’s set, when MACS failed to build paired model, it will use the nomodel settings, the ‘–extsize’ parameter to extend each tags. If set, MACS will be terminated if paired-peak model is failed.
default:False
settings.nomodel
label:Bypass building the shifting model
type:basic:boolean
description:While on, MACS will bypass building the shifting model.
hidden:tagalign
default:False
settings.nomodel_prepeak
label:Bypass building the shifting model
type:basic:boolean
description:While on, MACS will bypass building the shifting model.
hidden:!tagalign
default:True
settings.down_sample
label:Down-sample
type:basic:boolean
description:When set, random sampling method will scale down the bigger sample. By default, MACS uses linear scaling. This option will make the results unstable and irreproducible since each time, random reads would be selected, especially the numbers (pileup, pvalue, qvalue) would change. Consider to use ‘randsample’ script before MACS2 runs instead.
default:False
settings.bedgraph
label:Save fragment pileup and control lambda
type:basic:boolean
description:If this flag is on, MACS will store the fragment pileup, control lambda, -log10pvalue and -log10qvalue scores in bedGraph files. The bedGraph files will be stored in current directory named NAME+’_treat_pileup.bdg’ for treatment data, NAME+’_control_lambda.bdg’ for local lambda values from control, NAME+’_treat_pvalue.bdg’ for Poisson pvalue scores (in -log10(pvalue) form), and NAME+’_treat_qvalue.bdg’ for q-value scores from Benjamini-Hochberg-Yekutieli procedure.
default:True
settings.spmr
label:Save signal per million reads for fragment pileup profiles
type:basic:boolean
disabled:settings.bedgraph === false
default:True
settings.call_summits
label:Call summits
type:basic:boolean
description:MACS will now reanalyze the shape of signal profile (p or q-score depending on cutoff setting) to deconvolve subpeaks within each peak called from general procedure. It’s highly recommended to detect adjacent binding events. While used, the output subpeaks of a big peak region will have the same peak boundaries, and different scores and peak summit positions.
default:False
settings.broad
label:Composite broad regions
type:basic:boolean
description:When this flag is on, MACS will try to composite broad regions in BED12 (a gene-model-like format) by putting nearby highly enriched regions into a broad region with loose cutoff. The broad region is controlled by another cutoff through –broad-cutoff. The maximum length of broad region length is 4 times of d from MACS.
disabled:settings.call_summits === true
default:False
settings.broad_cutoff
label:Broad cutoff
type:basic:decimal
description:Cutoff for broad region. This option is not available unless –broad is set. If -p is set, this is a p-value cutoff, otherwise, it’s a q-value cutoff. DEFAULT = 0.1
required:False
disabled:settings.call_summits === true || settings.broad !== true
rose_settings.tss
label:TSS exclusion
type:basic:integer
description:Enter a distance from TSS to exclude. 0 = no TSS exclusion
default:0
rose_settings.stitch
label:Stitch
type:basic:integer
description:Enter a max linking distance for stitching. If not given, optimal stitching parameter will be determined automatically.
required:False
rose_settings.mask
label:Masking BED file
type:data:bed
description:Mask a set of regions from analysis. Provide a BED of masking regions.
required:False

Output results

Mappability
data:mappability:bcmmappability-bcm (data:genome:fasta  genome, data:annotation:gff3  gff, basic:integer  length)[Source: v2.0.1]

Compute genome mappability. Developed by Bioinformatics Laboratory, Faculty of Computer and Information Science, University of Ljubljana, Slovenia and Shaulsky’s Lab, Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA.

Input arguments

genome
label:Reference genome
type:data:genome:fasta
gff
label:General feature format
type:data:annotation:gff3
length
label:Read length
type:basic:integer
default:50

Output results

mappability
label:Mappability
type:basic:file
Mappability info
data:mappability:bcmupload-mappability (basic:file  src)[Source: v1.1.1]

Upload mappability information.

Input arguments

src
label:Mappability file
type:basic:file
description:Mappability file: 2 column tab separated
validate_regex:\.(tab)(|\.gz|\.bz2|\.tgz|\.tar\.gz|\.tar\.bz2|\.zip|\.rar|\.7z)$

Output results

mappability
label:Uploaded mappability
type:basic:file
Merge Expressions (ETC)
data:expressionset:etcmergeetc (list:data:etc  exps, list:basic:string  genes)[Source: v1.1.1]

Merge Expression Time Course (ETC) data.

Input arguments

exps
label:Expression Time Course (ETC)
type:list:data:etc
genes
label:Filter genes
type:list:basic:string
required:False

Output results

expset
label:Expression set
type:basic:file
expset_type
label:Expression set type
type:basic:string
Metabolic pathway file
data:metabolicpathwayupload-metabolic-pathway (basic:file  src, basic:string  source, basic:string  species)[Source: v1.0.1]

Upload pathway json.

Input arguments

src
label:Pathway file
type:basic:file
description:JSON file. Supported extensions: ‘.json’, ‘.json.gz’
validate_regex:(\.json)(\.gz)?$
source
label:Gene ID database
type:basic:string
choices:
  • BIGG: BIGG
species
label:Species
type:basic:string
choices:
  • Homo Sapiens: Homo Sapiens
  • Mus musculus: Mus musculus

Output results

pathway
label:Pathway json
type:basic:json
source
label:Gene ID database
type:basic:string
species
label:Species
type:basic:string
MultiQC
data:multiqcmultiqc (list:data  data, basic:boolean  dirs, basic:boolean  fullnames, basic:boolean  config, basic:string  cl_config)[Source: v1.1.2]

Aggregate results from bioinformatics analyses across many samples into a single report. [MultiQC](http://www.multiqc.info) searches a given directory for analysis logs and compiles a HTML report. It’s a general use tool, perfect for summarising the output from numerous bioinformatics tools.

Input arguments

data
label:Input data
type:list:data
description:Select multiple data objects for which the MultiQC report is to be generated.
advanced.dirs
label:–dirs
type:basic:boolean
description:Prepend directory to sample names.
default:True
advanced.fullnames
label:–fullnames
type:basic:boolean
description:Do not clean the sample names (leave as full file name).
default:False
advanced.config
label:Use configuration file
type:basic:boolean
description:Use Genialis configuration file for MultiQC report.
default:True
advanced.cl_config
label:–cl-config
type:basic:string
description:Enter text with command-line configuration options to override the defaults (e.g. custom_logo_url: https://www.genialis.com).
required:False

Output results

report
label:MultiQC report
type:basic:file:html
report_data
label:Report data
type:basic:dir
OBO file
data:ontology:oboupload-obo (basic:file  src)[Source: v1.1.1]

Upload gene ontology in OBO format.

Input arguments

src
label:Gene ontology (OBO)
type:basic:file
description:Gene ontology in OBO format.
required:True
validate_regex:\.obo(|\.gz|\.bz2|\.tgz|\.tar\.gz|\.tar\.bz2|\.zip|\.rar|\.7z)$

Output results

obo
label:Ontology file
type:basic:file
obo_obj
label:OBO object
type:basic:file
PCA
data:pcapca (list:data:expression  exps, list:basic:string  genes, basic:string  source, basic:string  species)[Source: v2.1.1]

Principal component analysis (PCA)

Input arguments

exps
label:Expressions
type:list:data:expression
genes
label:Gene subset
type:list:basic:string
required:False
source
label:Gene ID database of selected genes
type:basic:string
description:This field is required if gene subset is set.
required:False
species
label:Species
type:basic:string
description:Species latin name. This field is required if gene subset is set.
required:False
choices:
  • Homo sapiens: Homo sapiens
  • Mus musculus: Mus musculus
  • Rattus norvegicus: Rattus norvegicus
  • Dictyostelium discoideum: Dictyostelium discoideum
  • Odocoileus virginianus texanus: Odocoileus virginianus texanus
  • Solanum tuberosum: Solanum tuberosum

Output results

pca
label:PCA
type:basic:json
Picard CollectTargetedPcrMetrics
data:picard:coveragepicard-pcrmetrics (data:alignment:bam  alignment, data:masterfile:amplicon  master_file, data:genome:fasta  genome)[Source: v0.2.1]

Calculate PCR-related metrics from targeted sequencing data using the Picard CollectTargetedPcrMetrics tool

Input arguments

alignment
label:Alignment file (BAM)
type:data:alignment:bam
master_file
label:Master file
type:data:masterfile:amplicon
genome
label:Genome
type:data:genome:fasta

Output results

target_pcr_metrics
label:Target PCR metrics
type:basic:file
target_coverage
label:Target coverage
type:basic:file
Pre-peakcall QC
data:prepeakqcqc-prepeak (data:alignment:bam  alignment, basic:integer  q_treshold, basic:integer  n_sub, basic:boolean  tn5, basic:integer  shift)[Source: v0.2.2]

ChIP-Seq and ATAC-Seq QC metrics. Process returns a QC metrics report, fragment length estimation, and a deduplicated tagAlign file. Both fragment length estimation and the tagAlign file can be used as inputs in MACS 2.0. QC report contains ENCODE 3 proposed QC metrics – [NRF, PBC bottlenecking coefficients](https://www.encodeproject.org/data-standards/terms/), [NSC, and RSC](https://genome.ucsc.edu/ENCODE/qualityMetrics.html#chipSeq).

Input arguments

alignment
label:Aligned reads
type:data:alignment:bam
q_treshold
label:Quality filtering treshold
type:basic:integer
default:30
n_sub
label:Number of reads to subsample
type:basic:integer
default:15000000
tn5
label:TN5 shifting
type:basic:boolean
description:Tn5 transposon shifting. Shift reads on “+” strand by 4bp and reads on “-” strand by 5bp.
default:False
shift
label:User-defined cross-correlation peak strandshift
type:basic:integer
description:If defined, SPP tool will not try to estimate fragment length but will use the given value as fragment length.
required:False

Output results

chip_qc
label:QC report
type:basic:file
tagalign
label:Filtered tagAlign
type:basic:file
fraglen
label:Fragnment length
type:basic:integer
species
label:Species
type:basic:string
build
label:Build
type:basic:string
Prepare GEO - ChIP-Seq
data:other:geo:chipseqprepare-geo-chipseq (list:data:reads:fastq  reads, list:data:chipseq:callpeak  macs, basic:string  name)[Source: v2.0.2]

Prepare ChIP-seq data for GEO upload.

Input arguments

reads
label:Reads
type:list:data:reads:fastq
description:List of reads objects. Fastq files will be used.
macs
label:MACS
type:list:data:chipseq:callpeak
description:List of MACS2 or MACS14 objects. BedGraph (MACS2) or Wiggle (MACS14) files will be used.
name
label:Collection name
type:basic:string

Output results

tarball
label:GEO folder
type:basic:file
table
label:Annotation table
type:basic:file
Prepare GEO - RNA-Seq
data:other:geo:rnaseqprepare-geo-rnaseq (list:data:reads:fastq  reads, list:data:expression  expressions, basic:string  name)[Source: v0.1.1]

Prepare RNA-Seq data for GEO upload.

Input arguments

reads
label:Reads
type:list:data:reads:fastq
description:List of reads objects. Fastq files will be used.
expressions
label:Expressions
type:list:data:expression
description:Cuffnorm data object. Expression table will be used.
name
label:Collection name
type:basic:string

Output results

tarball
label:GEO folder
type:basic:file
table
label:Annotation table
type:basic:file
Quantify shRNA species using bowtie2
data:expression:shrna2quantshrna-quant (data:alignment:bam  alignment, basic:integer  readlengths, basic:integer  alignscores)[Source: v1.0.0]

Based on `bowtie2` output (.bam file) calculate number of mapped species. Input is limited to results from `bowtie2` since `YT:Z:` tag used to fetch aligned species is specific to this process. Result is a count matrix (successfully mapped reads) where species are in rows columns contain read specifics (count, species name, sequence, `AS:i:` tag value).

Input arguments

alignment
label:Alignment
type:data:alignment:bam
required:True
readlengths
label:Species lengths threshold
type:basic:integer
description:Species with read lengths below specified threshold will be removed from final output. Default is no removal.
alignscores
label:Align scores filter threshold
type:basic:integer
description:Species with align score below specified threshold will be removed from final output. Default is no removal.

Output results

exp
label:Normalized expression
type:basic:file
rc
label:Read counts
type:basic:file
required:False
exp_json
label:Expression (json)
type:basic:json
exp_type
label:Expression type
type:basic:string
source
label:Gene ID source
type:basic:string
species
label:Species
type:basic:string
build
label:Build
type:basic:string
feature_type
label:Feature type
type:basic:string
mapped_species
label:Mapped species
type:basic:file
RNA-Seq (Cuffquant)
data:workflow:rnaseq:cuffquantworkflow-rnaseq-cuffquant (data:reads:fastq  reads, data:genome:fasta  genome, data:annotation  annotation)[Source: v1.0.0]

Input arguments

reads
label:Input reads
type:data:reads:fastq
genome
label:genome
type:data:genome:fasta
annotation
label:Annotation file
type:data:annotation

Output results

ROSE2
data:chipseq:rose2rose2 (data:chipseq:callpeak  input, data:bed  input_upload, data:alignment:bam  rankby, data:alignment:bam  control, basic:integer  tss, basic:integer  stitch, data:bed  mask)[Source: v4.2.1]

For identification of super enhancers R2 uses the Rank Ordering of Super-Enhancers algorithm (ROSE2). This takes the peaks called by RSEG for acetylation and calculates the distances in-between to judge whether they can be considered super-enhancers. The ranked values can be plotted and by locating the inflection point in the resulting graph, super-enhancers can be assigned. It can also be used with the MACS calculated data. See [here](http://younglab.wi.mit.edu/super_enhancer_code.html) for more information.

Input arguments

input
label:BED/narrowPeak file (MACS results)
type:data:chipseq:callpeak
required:False
input_upload
label:BED file (Upload)
type:data:bed
required:False
rankby
label:BAM File
type:data:alignment:bam
description:bamfile to rank enhancer by
control
label:Control BAM File
type:data:alignment:bam
description:bamfile to rank enhancer by
required:False
tss
label:TSS exclusion
type:basic:integer
description:Enter a distance from TSS to exclude. 0 = no TSS exclusion
default:0
stitch
label:Stitch
type:basic:integer
description:Enter a max linking distance for stitching. If not given, optimal stitching parameter will be determined automatically.
required:False
mask
label:Masking BED file
type:data:bed
description:Mask a set of regions from analysis. Provide a BED of masking regions.
required:False

Output results

all_enhancers
label:All enhancers table
type:basic:file
enhancers_with_super
label:Super enhancers table
type:basic:file
plot_points
label:Plot points
type:basic:file
plot_panel
label:Plot panel
type:basic:file
enhancer_gene
label:Enhancer to gene
type:basic:file
enhancer_top_gene
label:Enhancer to top gene
type:basic:file
gene_enhancer
label:Gene to Enhancer
type:basic:file
stitch_parameter
label:Stitch parameter
type:basic:file
required:False
all_output
label:All output
type:basic:file
scatter_plot
label:Super-Enhancer plot
type:basic:json
species
label:Species
type:basic:string
build
label:Build
type:basic:string
RSEM
data:expression:rsemrsem (data:alignment:bam  alignments, basic:string  read_type, data:index:expression  expression_index, basic:string  strandedness)[Source: v1.1.1]

RSEM is a software package for estimating gene and isoform expression levels from RNA-Seq data. The RSEM package supports threads for parallel computation of the EM algorithm, single-end and paired-end read data, quality scores, variable-length reads and RSPD estimation. See [here](https://deweylab.github.io/RSEM/README.html) and the [original paper](https://bmcbioinformatics.biomedcentral.com/articles/10.1186/1471-2105-12-323) for more information.

Input arguments

alignments
label:Aligned reads
type:data:alignment:bam
read_type
label:Type of reads
type:basic:string
default:se
choices:
  • Single-end: se
  • Paired-end: pe
expression_index
label:Gene expression indices
type:data:index:expression
strandedness
label:Strandedness
type:basic:string
default:none
choices:
  • None: none
  • Forward: forward
  • Reverse: reverse

Output results

rc
label:Read counts
type:basic:file
fpkm
label:FPKM
type:basic:file
exp
label:TPM (Transcripts Per Million)
type:basic:file
exp_json
label:TPM (json)
type:basic:json
exp_set
label:Expressions
type:basic:file
exp_set_json
label:Expressions (json)
type:basic:json
genes
label:Results grouped by gene
type:basic:file
transcripts
label:Results grouped by transcript
type:basic:file
log
label:RSEM log
type:basic:file
exp_type
label:Type of expression
type:basic:string
source
label:Transcript ID database
type:basic:string
species
label:Species
type:basic:string
build
label:Build
type:basic:string
feature_type
label:Feature type
type:basic:string
Reads (QSEQ multiplexed, paired)
data:multiplexed:qseq:pairedupload-multiplexed-paired (basic:file  reads, basic:file  reads2, basic:file  barcodes, basic:file  annotation)[Source: v1.1.1]

Upload multiplexed NGS reds in QSEQ format.

Input arguments

reads
label:Multiplexed upstream reads
type:basic:file
description:NGS reads in QSeq format. Supported extensions: .qseq.txt.bz2 (preferred), .qseq.* or .qseq.txt.*.
required:True
validate_regex:((\.qseq|\.qseq\.txt)(\.gz|\.bz2|\.tgz|\.tar\.gz|\.tar\.bz2|\.zip|\.rar|\.7z))|(\.bz2)$
reads2
label:Multiplexed downstream reads
type:basic:file
description:NGS reads in QSeq format. Supported extensions: .qseq.txt.bz2 (preferred), .qseq.* or .qseq.txt.*.
required:True
validate_regex:((\.qseq|\.qseq\.txt)(\.gz|\.bz2|\.tgz|\.tar\.gz|\.tar\.bz2|\.zip|\.rar|\.7z))|(\.bz2)$
barcodes
label:NGS barcodes
type:basic:file
description:Barcodes in QSeq format. Supported extensions: .qseq.txt.bz2 (preferred), .qseq.* or .qseq.txt.*.
required:True
validate_regex:((\.qseq|\.qseq\.txt)(\.gz|\.bz2|\.tgz|\.tar\.gz|\.tar\.bz2|\.zip|\.rar|\.7z))|(\.bz2)$
annotation
label:Barcode mapping
type:basic:file
description:A tsv file mapping barcodes to experiment name, e.g. “TCGCAGG\tHr00”.
required:True
validate_regex:(\.csv|\.tsv)$

Output results

qseq_reads
label:Multiplexed upstream reads
type:basic:file
qseq_reads2
label:Multiplexed downstream reads
type:basic:file
qseq_barcodes
label:NGS barcodes
type:basic:file
annotation
label:Barcode mapping
type:basic:file
matched
label:Matched
type:basic:string
notmatched
label:Not matched
type:basic:string
badquality
label:Bad quality
type:basic:string
skipped
label:Skipped
type:basic:string
Reads (QSEQ multiplexed, single)
data:multiplexed:qseq:singleupload-multiplexed-single (basic:file  reads, basic:file  barcodes, basic:file  annotation)[Source: v1.1.1]

Upload multiplexed NGS reds in QSEQ format.

Input arguments

reads
label:Multiplexed NGS reads
type:basic:file
description:NGS reads in QSeq format. Supported extensions: .qseq.txt.bz2 (preferred), .qseq.* or .qseq.txt.*.
required:True
validate_regex:(\.(qseq)(|\.txt)(|\.gz|\.bz2|\.tgz|\.tar\.gz|\.tar\.bz2|\.zip|\.rar|\.7z))|(\.bz2)$
barcodes
label:NGS barcodes
type:basic:file
description:Barcodes in QSeq format. Supported extensions: .qseq.txt.bz2 (preferred), .qseq.* or .qseq.txt.*.
required:True
validate_regex:(\.(qseq)(|\.txt)(|\.gz|\.bz2|\.tgz|\.tar\.gz|\.tar\.bz2|\.zip|\.rar|\.7z))|(\.bz2)$
annotation
label:Barcode mapping
type:basic:file
description:A tsv file mapping barcodes to experiment name, e.g. “TCGCAGG\tHr00”.
required:True
validate_regex:(\.csv|\.tsv)$

Output results

qseq_reads
label:Multiplexed NGS reads
type:basic:file
qseq_barcodes
label:NGS barcodes
type:basic:file
annotation
label:Barcode mapping
type:basic:file
matched
label:Matched
type:basic:string
notmatched
label:Not matched
type:basic:string
badquality
label:Bad quality
type:basic:string
skipped
label:Skipped
type:basic:string
SAM header
data:sam:headerupload-header-sam (basic:file  src)[Source: v1.1.1]

Upload a mapping file header in SAM format.

Input arguments

src
label:Header (SAM)
type:basic:file
description:A mapping file header in SAM format.
validate_regex:\.(sam)$

Output results

sam
label:Uploaded file
type:basic:file
SRA data
data:sraimport-sra (basic:string  sra_accession, basic:boolean  show_advanced, basic:integer  min_spot_id, basic:integer  max_spot_id, basic:integer  min_read_len, basic:boolean  clip, basic:boolean  aligned, basic:boolean  unaligned)[Source: v0.1.1]

Import single or paired-end reads from Sequence Read Archive (SRA) via an SRA accession number. SRA stores raw sequencing data and alignment information from high-throughput sequencing platforms.

Input arguments

sra_accession
label:SRA accession
type:basic:string
show_advanced
label:Show advanced options
type:basic:boolean
default:False
advanced.min_spot_id
label:Minimum spot ID
type:basic:integer
required:False
advanced.max_spot_id
label:Maximum spot ID
type:basic:integer
required:False
advanced.min_read_len
label:Minimum read length
type:basic:integer
required:False
advanced.clip
label:Clip adapter sequences
type:basic:boolean
default:False
advanced.aligned
label:Dump only aligned sequences
type:basic:boolean
default:False
advanced.unaligned
label:Dump only unaligned sequences
type:basic:boolean
default:False

Output results

SRA data (paired-end)
data:reads:fastq:pairedimport-sra-paired (basic:string  sra_accession, basic:boolean  show_advanced, basic:integer  min_spot_id, basic:integer  max_spot_id, basic:integer  min_read_len, basic:boolean  clip, basic:boolean  aligned, basic:boolean  unaligned)[Source: v0.1.1]

Import paired-end reads from Sequence Read Archive (SRA) via an SRA accession number. SRA stores raw sequencing data and alignment information from high-throughput sequencing platforms.

Input arguments

sra_accession
label:SRA accession
type:basic:string
show_advanced
label:Show advanced options
type:basic:boolean
default:False
advanced.min_spot_id
label:Minimum spot ID
type:basic:integer
required:False
advanced.max_spot_id
label:Maximum spot ID
type:basic:integer
required:False
advanced.min_read_len
label:Minimum read length
type:basic:integer
required:False
advanced.clip
label:Clip adapter sequences
type:basic:boolean
default:False
advanced.aligned
label:Dump only aligned sequences
type:basic:boolean
default:False
advanced.unaligned
label:Dump only unaligned sequences
type:basic:boolean
default:False

Output results

fastq
label:Reads file (mate 1)
type:list:basic:file
fastq2
label:Reads file (mate 2)
type:list:basic:file
fastqc_url
label:Quality control with FastQC (Upstream)
type:list:basic:file:html
fastqc_url2
label:Quality control with FastQC (Downstream)
type:list:basic:file:html
fastqc_archive
label:Download FastQC archive (Upstream)
type:list:basic:file
fastqc_archive2
label:Download FastQC archive (Downstream)
type:list:basic:file
SRA data (single-end)
data:reads:fastq:singleimport-sra-single (basic:string  sra_accession, basic:boolean  show_advanced, basic:integer  min_spot_id, basic:integer  max_spot_id, basic:integer  min_read_len, basic:boolean  clip, basic:boolean  aligned, basic:boolean  unaligned)[Source: v0.1.1]

Import single-end reads from Sequence Read Archive (SRA) via an SRA accession number. SRA stores raw sequencing data and alignment information from high-throughput sequencing platforms.

Input arguments

sra_accession
label:SRA accession
type:basic:string
show_advanced
label:Show advanced options
type:basic:boolean
default:False
advanced.min_spot_id
label:Minimum spot ID
type:basic:integer
required:False
advanced.max_spot_id
label:Maximum spot ID
type:basic:integer
required:False
advanced.min_read_len
label:Minimum read length
type:basic:integer
required:False
advanced.clip
label:Clip adapter sequences
type:basic:boolean
default:False
advanced.aligned
label:Dump only aligned sequences
type:basic:boolean
default:False
advanced.unaligned
label:Dump only unaligned sequences
type:basic:boolean
default:False

Output results

fastq
label:Reads file
type:list:basic:file
fastqc_url
label:Quality control with FastQC
type:list:basic:file:html
fastqc_archive
label:Download FastQC archive
type:list:basic:file
STAR
data:alignment:bam:staralignment-star (data:reads:fastq  reads, data:genomeindex:star  genome, data:annotation  annotation, basic:string  exon_name, basic:integer  sjdbOverhang, basic:boolean  unstranded, basic:boolean  noncannonical, basic:boolean  chimeric, basic:integer  chimSegmentMin, basic:boolean  quantmode, basic:boolean  singleend, basic:boolean  gene_counts, basic:string  outFilterType, basic:integer  outFilterMultimapNmax, basic:integer  outFilterMismatchNmax, basic:decimal  outFilterMismatchNoverLmax, basic:integer  outFilterScoreMin, basic:decimal  outFilterMismatchNoverReadLmax, basic:integer  alignSJoverhangMin, basic:integer  alignSJDBoverhangMin, basic:integer  alignIntronMin, basic:integer  alignIntronMax, basic:integer  alignMatesGapMax, basic:string  alignEndsType, basic:boolean  two_pass_mode, basic:string  outSAMunmapped, basic:string  outSAMattributes, basic:string  outSAMattrRGline, basic:string  tool_bigwig, basic:integer  bin_size_bigwig)[Source: v1.8.11]

Spliced Transcripts Alignment to a Reference (STAR) software is based on an alignment algorithm that uses sequential maximum mappable seed search in uncompressed suffix arrays followed by seed clustering and stitching procedure. In addition to unbiased de novo detection of canonical junctions, STAR can discover non-canonical splices and chimeric (fusion) transcripts, and is also capable of mapping full-length RNA sequences. More information can be found in the [STAR manual](http://labshare.cshl.edu/shares/gingeraslab/www-data/dobin/STAR/STAR.posix/doc/STARmanual.pdf) and in the [original paper](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3530905/).

Input arguments

reads
label:Reads
type:data:reads:fastq
genome
label:Indexed reference genome
type:data:genomeindex:star
description:Genome index prepared by STAR aligner indexing tool.
annotation
label:Annotation file (GTF/GFF3)
type:data:annotation
description:Insert known annotations into genome indices at the mapping stage.
required:False
annotation_options.exon_name
label:–sjdbGTFfeatureExon
type:basic:string
description:Feature type in GTF file to be used as exons for building transcripts
default:exon
annotation_options.sjdbOverhang
label:Junction length (sjdbOverhang)
type:basic:integer
description:This parameter specifies the length of the genomic sequence around the annotated junction to be used in constructing the splice junction database. Ideally, this length should be equal to the ReadLength-1, where ReadLength is the length of the reads. For instance, for Illumina 2x100b paired-end reads, the ideal value is 100-1=99. In case of reads of varying length, the ideal value is max(ReadLength)-1. In most cases, the default value of 100 will work as well as the ideal value.
default:100
unstranded
label:The data is unstranded
type:basic:boolean
description:For unstranded RNA-seq data, Cufflinks/Cuffdiff require spliced alignments with XS strand attribute, which STAR will generate with –outSAMstrandField intronMotif option. As required, the XS strand attribute will be generated for all alignments that contain splice junctions. The spliced alignments that have undefined strand (i.e. containing only non-canonical unannotated junctions) will be suppressed. If you have stranded RNA-seq data, you do not need to use any specific STAR options. Instead, you need to run Cufflinks with the library option –library-type options. For example, cufflinks –library-type fr-firststrand should be used for the standard dUTP protocol, including Illumina’s stranded Tru-Seq. This option has to be used only for Cufflinks runs and not for STAR runs.
default:False
noncannonical
label:Remove non-cannonical junctions (Cufflinks compatibility)
type:basic:boolean
description:It is recommended to remove the non-canonical junctions for Cufflinks runs using –outFilterIntronMotifs RemoveNoncanonical.
default:False
detect_chimeric.chimeric
label:Detect chimeric and circular alignments
type:basic:boolean
description:To switch on detection of chimeric (fusion) alignments (in addition to normal mapping), –chimSegmentMin should be set to a positive value. Each chimeric alignment consists of two “segments”. Each segment is non-chimeric on its own, but the segments are chimeric to each other (i.e. the segments belong to different chromosomes, or different strands, or are far from each other). Both segments may contain splice junctions, and one of the segments may contain portions of both mates. –chimSegmentMin parameter controls the minimum mapped length of the two segments that is allowed. For example, if you have 2x75 reads and used –chimSegmentMin 20, a chimeric alignment with 130b on one chromosome and 20b on the other will be output, while 135 + 15 won’t be.
default:False
detect_chimeric.chimSegmentMin
label:–chimSegmentMin
type:basic:integer
disabled:detect_chimeric.chimeric != true
default:20
t_coordinates.quantmode
label:Output in transcript coordinates
type:basic:boolean
description:With –quantMode TranscriptomeSAM option STAR will output alignments translated into transcript coordinates in the Aligned.toTranscriptome.out.bam file (in addition to alignments in genomic coordinates in Aligned.*.sam/bam files). These transcriptomic alignments can be used with various transcript quantification software that require reads to be mapped to transcriptome, such as RSEM or eXpress.
default:False
t_coordinates.singleend
label:Allow soft-clipping and indels
type:basic:boolean
description:By default, the output satisfies RSEM requirements: soft-clipping or indels are not allowed. Use –quantTranscriptomeBan Singleend to allow insertions, deletions ans soft-clips in the transcriptomic alignments, which can be used by some expression quantification software (e.g. eXpress).
disabled:t_coordinates.quantmode != true
default:False
t_coordinates.gene_counts
label:Count reads
type:basic:boolean
description:With –quantMode GeneCounts option STAR will count number reads per gene while mapping. A read is counted if it overlaps (1nt or more) one and only one gene. Both ends of the paired-end read are checked for overlaps. The counts coincide with those produced by htseq-count with default parameters. ReadsPerGene.out.tab file with 4 columns which correspond to different strandedness options: column 1: gene ID; column 2: counts for unstranded RNA-seq; column 3: counts for the 1st read strand aligned with RNA (htseq-count option -s yes); column 4: counts for the 2nd read strand aligned with RNA (htseq-count option -s reverse).
disabled:t_coordinates.quantmode != true
default:False
filtering.outFilterType
label:Type of filtering
type:basic:string
description:Normal: standard filtering using only current alignment; BySJout: keep only those reads that contain junctions that passed filtering into SJ.out.tab
default:Normal
choices:
  • Normal: Normal
  • BySJout: BySJout
filtering.outFilterMultimapNmax
label:–outFilterMultimapNmax
type:basic:integer
description:Read alignments will be output only if the read maps fewer than this value, otherwise no alignments will be output (default: 10).
required:False
filtering.outFilterMismatchNmax
label:–outFilterMismatchNmax
type:basic:integer
description:Alignment will be output only if it has fewer mismatches than this value (default: 10).
required:False
filtering.outFilterMismatchNoverLmax
label:–outFilterMismatchNoverLmax
type:basic:decimal
description:Max number of mismatches per pair relative to read length: for 2x100b, max number of mismatches is 0.06*200=8 for the paired read.
required:False
filtering.outFilterScoreMin
label:–outFilterScoreMin
type:basic:integer
description:Alignment will be output only if its score is higher than or equal to this value (default: 0).
required:False
filtering.outFilterMismatchNoverReadLmax
label:–outFilterMismatchNoverReadLmax
type:basic:decimal
description:Alignment will be output only if its ratio of mismatches to *read* length is less than or equal to this value (default: 1.0).
required:False
alignment.alignSJoverhangMin
label:–alignSJoverhangMin
type:basic:integer
description:Minimum overhang (i.e. block size) for spliced alignments (default: 5).
required:False
alignment.alignSJDBoverhangMin
label:–alignSJDBoverhangMin
type:basic:integer
description:Minimum overhang (i.e. block size) for annotated (sjdb) spliced alignments (default: 3).
required:False
alignment.alignIntronMin
label:–alignIntronMin
type:basic:integer
description:Minimum intron size: genomic gap is considered intron if its length >= alignIntronMin, otherwise it is considered Deletion (default: 21).
required:False
alignment.alignIntronMax
label:–alignIntronMax
type:basic:integer
description:Maximum intron size, if 0, max intron size will be determined by (2pow(winBinNbits)*winAnchorDistNbins) (default: 0).
required:False
alignment.alignMatesGapMax
label:–alignMatesGapMax
type:basic:integer
description:Maximum gap between two mates, if 0, max intron gap will be determined by (2pow(winBinNbits)*winAnchorDistNbins) (default: 0).
required:False
alignment.alignEndsType
label:–alignEndsType
type:basic:string
description:Type of read ends alignment (default: Local).
required:False
default:Local
choices:
  • Local: Local
  • EndToEnd: EndToEnd
  • Extend5pOfRead1: Extend5pOfRead1
  • Extend5pOfReads12: Extend5pOfReads12
two_pass_mapping.two_pass_mode
label:–twopassMode
type:basic:boolean
description:Perform first-pass mapping, extract junctions, insert them into genome index, and re-map all reads in the second mapping pass.
default:False
output_sam_bam.outSAMunmapped
label:–outSAMunmapped
type:basic:string
description:Output of unmapped reads in the SAM format.
required:False
default:None
choices:
  • None: None
  • Within: Within
output_sam_bam.outSAMattributes
label:–outSAMattributes
type:basic:string
description:a string of desired SAM attributes, in the order desired for the output SAM.
required:False
default:Standard
choices:
  • None: None
  • Standard: Standard
  • All: All
output_sam_bam.outSAMattrRGline
label:–outSAMattrRGline
type:basic:string
description:SAM/BAM read group line. The first word contains the read group identifier and must start with “ID:”, e.g. –outSAMattrRGline ID:xxx CN:yy “DS:z z z”
required:False
output_sam_bam.tool_bigwig
label:Tool to calculate BigWig
type:basic:string
description:Tool to calculate BigWig.
default:deeptools
choices:
  • deepTools: deeptools
  • UCSC BedGraphToBigWig: bedgraphtobigwig
output_sam_bam.bin_size_bigwig
label:Bin Size for the output of BigWig
type:basic:integer
description:Size of the bins, in bases, for the output of the bigwig. Only possible if ‘Tool to calculate BigWig’ is deepTools. If BigWig is calculated by UCSC BedGraphToBigWig then bin size is 1.
default:50

Output results

bam
label:Alignment file
type:basic:file
description:Position sorted alignment
bai
label:Index BAI
type:basic:file
unmapped_f
label:Unmapped reads (mate 1)
type:basic:file
required:False
unmapped_r
label:Unmapped reads (mate 2)
type:basic:file
required:False
sj
label:Splice junctions
type:basic:file
chimeric
label:Chimeric alignments
type:basic:file
required:False
alignment_transcriptome
label:Alignment (trancriptome coordinates)
type:basic:file
required:False
gene_counts
label:Gene counts
type:basic:file
required:False
stats
label:Statistics
type:basic:file
bigwig
label:BigWig file
type:basic:file
required:False
species
label:Species
type:basic:string
build
label:Build
type:basic:string
STAR genome index
data:genomeindex:staralignment-star-index (data:genome:fasta  genome, data:seq:nucleotide  genome2, data:annotation  annotation, basic:string  exon_name, basic:integer  sjdbOverhang, basic:integer  genomeSAindexNbases, basic:integer  genomeChrBinNbits, basic:integer  genomeSAsparseD)[Source: v1.5.4]

Generate genome indices files from the supplied reference genome sequence and GTF files.

Input arguments

genome
label:Reference genome (indexed)
type:data:genome:fasta
required:False
genome2
label:Reference genome (nucleotide sequence)
type:data:seq:nucleotide
required:False
annotation
label:Annotation file (GTF/GFF3)
type:data:annotation
required:False
annotation_options.exon_name
label:–sjdbGTFfeatureExon
type:basic:string
description:Feature type in GTF file to be used as exons for building transcripts.
default:exon
annotation_options.sjdbOverhang
label:Junction length (sjdbOverhang)
type:basic:integer
description:This parameter specifies the length of the genomic sequence around the annotated junction to be used in constructing the splice junction database. Ideally, this length should be equal to the ReadLength-1, where ReadLength is the length of the reads. For instance, for Illumina 2x100b paired-end reads, the ideal value is 100-1=99. In case of reads of varying length, the ideal value is max(ReadLength)-1. In most cases, the default value of 100 will work as well as the ideal value.
default:100
advanced.genomeSAindexNbases
label:Small genome adjustment
type:basic:integer
description:For small genomes, the parameter –genomeSAindexNbases needs to be scaled down, with a typical value of min(14, log2(GenomeLength)/2 - 1). For example, for 1 megaBase genome, this is equal to 9, for 100 kiloBase genome, this is equal to 7.
required:False
advanced.genomeChrBinNbits
label:Large number of references adjustment
type:basic:integer
description:If you are using a genome with a large (>5,000) number of references (chrosomes/scaffolds), you may need to reduce the –genomeChrBinNbits to reduce RAM consumption. The following scaling is recommended: –genomeChrBinNbits = min(18, log2(GenomeLength / NumberOfReferences)). For example, for 3 gigaBase genome with 100,000 chromosomes/scaffolds, this is equal to 15.
required:False
advanced.genomeSAsparseD
label:Sufflux array sparsity
type:basic:integer
description:Suffux array sparsity, i.e. distance between indices: use bigger numbers to decrease needed RAM at the cost of mapping speed reduction (integer > 0, default = 1).
required:False

Output results

index
label:Indexed genome
type:basic:dir
source
label:Gene ID source
type:basic:string
species
label:Species
type:basic:string
build
label:Build
type:basic:string
Salmon Index
data:index:salmonsalmon-index (data:seq:nucleotide  nucl, data:file  decoys, basic:boolean  gencode, basic:boolean  keep_duplicates, basic:boolean  perfect_hash, basic:string  source, basic:string  species, basic:string  build, basic:integer  kmerlen)[Source: v1.0.0]

Generate index files for Salmon transcript quantification tool.

Input arguments

nucl
label:Nucleotide sequence
type:data:seq:nucleotide
description:A CDS sequence file in .FASTA format.
decoys
label:Decoys
type:data:file
description:Treat these sequences as decoys that may have sequence homologous to some known transcript.
required:False
gencode
label:Gencode
type:basic:boolean
description:This flag will expect the input transcript FASTA to be in GENCODE format, and will split the transcript name at the first ‘|’ character. These reduced names will be used in the output and when looking for these transcripts in a gene to transcript GTF.
default:False
keep_duplicates
label:Keep duplicates
type:basic:boolean
description:This flag will disable the default indexing behavior of discarding sequence-identical duplicate transcripts. If this flag is passed, then duplicate transcripts that appear in the input will be retained and quantified separately.
default:False
perfect_hash
label:Perfect hash
type:basic:boolean
description:Build the index using a perfect hash rather than a dense hash. This will require less memory (especially during quantification), but will take longer to construct.
default:False
source
label:Source of attribute ID
type:basic:string
choices:
  • DICTYBASE: DICTYBASE
  • ENSEMBL: ENSEMBL
  • NCBI: NCBI
  • UCSC: UCSC
species
label:Species
type:basic:string
description:Species latin name.
choices:
  • Homo sapiens: Homo sapiens
  • Mus musculus: Mus musculus
  • Rattus norvegicus: Rattus norvegicus
  • Dictyostelium discoideum: Dictyostelium discoideum
build
label:Genome build
type:basic:string
kmerlen
label:Size of k-mers
type:basic:integer
description:The size of k-mers that should be used for the quasi index. We find that a k of 31 seems to work well for reads of 75bp or longer, but you might consider a smaller k if you plan to deal with shorter reads.
default:31

Output results

index
label:Salmon index
type:basic:dir
source
label:Source of attribute ID
type:basic:string
species
label:Species
type:basic:string
build
label:Build
type:basic:string
Secondary hybrid BAM file
data:alignment:bam:secondaryupload-bam-secondary (data:alignment:bam  bam, basic:file  src, basic:string  species, basic:string  build)[Source: v0.5.0]

Upload a secondary mapping file in BAM format.

Input arguments

bam
label:Hybrid bam
type:data:alignment:bam
description:Secondary bam will be appended to the same sample where hybrid bam is.
required:False
src
label:Mapping (BAM)
type:basic:file
description:A mapping file in BAM format. The file will be indexed on upload, so additional BAI files are not required.
validate_regex:\.(bam)$
species
label:Species
type:basic:string
description:Species latin name.
choices:
  • Drosophila melanogaster: Drosophila melanogaster
  • Mus musculus: Mus musculus
build
label:Build
type:basic:string

Output results

bam
label:Uploaded file
type:basic:file
bai
label:Index BAI
type:basic:file
stats
label:Alignment statistics
type:basic:file
bigwig
label:BigWig file
type:basic:file
required:False
species
label:Species
type:basic:string
build
label:Build
type:basic:string
Spike-ins quality control
data:spikeinsspikein-qc (list:data:expression  samples, basic:string  mix)[Source: v0.0.3]

Plot spike-ins measured abundances for samples quality control. The process will output graphs showing the correlation between known concentration of ERCC spike-ins and sample’s measured abundance.

Input arguments

samples
label:Expressions with spike-ins
type:list:data:expression
mix
label:Spike-ins mix
type:basic:string
description:Select spike-ins mix.
choices:
  • ERCC Mix 1: ercc_mix1
  • ERCC Mix 2: ercc_mix2
  • SIRV-Set 3: sirv_set3

Output results

plots
label:Plot figures
type:list:basic:file
report
label:HTML report with results
type:basic:file:html
hidden:True
report_zip
label:ZIP file contining HTML report with results
type:basic:file
Subread
data:alignment:bam:subreadalignment-subread (data:genome:fasta  genome, data:reads:fastq  reads, basic:integer  indel, basic:integer  consensus, basic:integer  mis_matched_bp, basic:integer  cpu_number, basic:boolean  multi_mapping, basic:string  reads_orientation, basic:integer  consensus_subreads)[Source: v2.1.1]

Subread is an accurate and efficient general-purpose read aligner which can align both genomic DNA-seq and RNA-seq reads. It can also be used to discover genomic mutations including short indels and structural variants. See [here](http://subread.sourceforge.net/) and a paper by [Liao and colleagues](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3664803/) (2013) for more information.

Input arguments

genome
label:Reference genome
type:data:genome:fasta
reads
label:Reads
type:data:reads:fastq
options.indel
label:Number of INDEL bases
type:basic:integer
description:Specify the number of INDEL bases allowed in the mapping.
required:False
default:5
options.consensus
label:Consensus threshold
type:basic:integer
description:Specify the consensus threshold, which is the minimal number of consensus subreads required for reporting a hit.
required:False
default:3
options.mis_matched_bp
label:Max number of mis-matched bases
type:basic:integer
description:Specify the maximum number of mis-matched bases allowed in the alignment.
required:False
default:3
options.cpu_number
label:Number of threads/CPUs
type:basic:integer
description:Specify the number of threads/CPUs used for mapping
required:False
default:1
options.multi_mapping
label:Report multi-mapping reads in addition to uniquely mapped reads.
type:basic:boolean
description:Reads that were found to have more than one best mapping location are going to be reported.
required:False
PE_options.reads_orientation
label:reads orientation
type:basic:string
description:Specify the orientation of the two reads from the same pair.
required:False
default:fr
choices:
  • ff: ff
  • fr: fr
  • rf: rf
PE_options.consensus_subreads
label:Minimum number of consensus subreads
type:basic:integer
description:Specify the minimum number of consensus subreads both reads from the sam pair must have.
required:False
default:1

Output results

bam
label:Alignment file
type:basic:file
description:Position sorted alignment
bai
label:Index BAI
type:basic:file
unmapped
label:Unmapped reads
type:basic:file
required:False
stats
label:Statistics
type:basic:file
bigwig
label:BigWig file
type:basic:file
required:False
species
label:Species
type:basic:string
build
label:Build
type:basic:string
Subsample FASTQ (paired-end)
data:reads:fastq:paired:seqtkseqtk-sample-paired (data:reads:fastq:paired  reads, basic:integer  n_reads, basic:integer  seed, basic:decimal  fraction, basic:boolean  two_pass)[Source: v1.0.3]

[Seqtk](https://github.com/lh3/seqtk) is a fast and lightweight tool for processing sequences in the FASTA or FASTQ format. The Seqtk “sample” command enables subsampling of the large FASTQ file(s).

Input arguments

reads
label:Reads
type:data:reads:fastq:paired
n_reads
label:Number of reads
type:basic:integer
default:1000000
advanced.seed
label:Seed
type:basic:integer
default:11
advanced.fraction
label:Fraction
type:basic:decimal
description:Use the fraction of reads [0 - 1.0] from the orignal input file instead of the absolute number of reads. If set, this will override the “Number of reads” input parameter.
required:False
advanced.two_pass
label:2-pass mode
type:basic:boolean
description:Enable two-pass mode when down-sampling. Two-pass mode is twice as slow but with much reduced memory.
default:False

Output results

fastq
label:Remaining mate 1 reads
type:list:basic:file
fastq2
label:Remaining mate 2 reads
type:list:basic:file
fastqc_url
label:Mate 1 quality control with FastQC
type:list:basic:file:html
fastqc_url2
label:Mate 2 quality control with FastQC
type:list:basic:file:html
fastqc_archive
label:Download mate 1 FastQC archive
type:list:basic:file
fastqc_archive2
label:Download mate 2 FastQC archive
type:list:basic:file
Subsample FASTQ (single-end)
data:reads:fastq:single:seqtkseqtk-sample-single (data:reads:fastq:single  reads, basic:integer  n_reads, basic:integer  seed, basic:decimal  fraction, basic:boolean  two_pass)[Source: v1.0.3]

[Seqtk](https://github.com/lh3/seqtk) is a fast and lightweight tool for processing sequences in the FASTA or FASTQ format. The Seqtk “sample” command enables subsampling of the large FASTQ file(s).

Input arguments

reads
label:Reads
type:data:reads:fastq:single
n_reads
label:Number of reads
type:basic:integer
default:1000000
advanced.seed
label:Seed
type:basic:integer
default:11
advanced.fraction
label:Fraction
type:basic:decimal
description:Use the fraction of reads [0 - 1.0] from the orignal input file instead of the absolute number of reads. If set, this will override the “Number of reads” input parameter.
required:False
advanced.two_pass
label:2-pass mode
type:basic:boolean
description:Enable two-pass mode when down-sampling. Two-pass mode is twice as slow but with much reduced memory.
default:False

Output results

fastq
label:Remaining reads
type:list:basic:file
fastqc_url
label:Quality control with FastQC
type:list:basic:file:html
fastqc_archive
label:Download FastQC archive
type:list:basic:file
Test basic fields
data:test:fieldstest-basic-fields (basic:boolean  boolean, basic:date  date, basic:datetime  datetime, basic:decimal  decimal, basic:integer  integer, basic:string  string, basic:text  text, basic:url:download  url_download, basic:url:view  url_view, basic:string  string2, basic:string  string3, basic:string  string4, basic:string  string5, basic:string  string6, basic:string  string7, basic:string  tricky2)[Source: v1.1.1]

Test with all basic input fields whose values are printed by the processor and returned unmodified as output fields.

Input arguments

boolean
label:Boolean
type:basic:boolean
default:True
date
label:Date
type:basic:date
default:2013-12-31
datetime
label:Date and time
type:basic:datetime
default:2013-12-31 23:59:59
decimal
label:Decimal
type:basic:decimal
default:-123.456
integer
label:Integer
type:basic:integer
default:-123
string
label:String
type:basic:string
default:Foo b-a-r.gz 1.23
text
label:Text
type:basic:text
default:Foo bar in 3 lines.
url_download
label:URL download
type:basic:url:download
default:{'url': 'http://www.w3.org/TR/1998/REC-html40-19980424/html40.pdf'}
url_view
label:URL view
type:basic:url:view
default:{'name': 'Something', 'url': 'http://www.something.com/'}
group.string2
label:String 2 required
type:basic:string
description:String 2 description.
required:True
disabled:false
hidden:false
placeholder:Enter string
group.string3
label:String 3 disabled
type:basic:string
description:String 3 description.
disabled:true
default:disabled
group.string4
label:String 4 hidden
type:basic:string
description:String 4 description.
hidden:True
default:hidden
group.string5
label:String 5 choices
type:basic:string
description:String 5 description.
hidden:False
default:choice_2
choices:
  • Choice 1: choice_1
  • Choice 2: choice_2
  • Choice 3: choice_3
group.string6
label:String 6 regex only “Aa”
type:basic:string
default:AAaAaaa
validate_regex:^[aA]*$
group.string7
label:String 7 optional choices
type:basic:string
description:String 7 description.
required:False
hidden:False
default:choice_2
choices:
  • Choice 1: choice_1
  • Choice 2: choice_2
  • Choice 3: choice_3
tricky.tricky1.tricky2
label:Tricky 2
type:basic:string
default:true

Output results

output
label:Result
type:basic:url:view
out_boolean
label:Boolean
type:basic:boolean
out_date
label:Date
type:basic:date
out_datetime
label:Date and time
type:basic:datetime
out_decimal
label:Decimal
type:basic:decimal
out_integer
label:Integer
type:basic:integer
out_string
label:String
type:basic:string
out_text
label:Text
type:basic:text
out_url_download
label:URL download
type:basic:url:download
out_url_view
label:URL view
type:basic:url:view
out_group.string2
label:String 2 required
type:basic:string
description:String 2 description.
out_group.string3
label:String 3 disabled
type:basic:string
description:String 3 description.
out_group.string4
label:String 4 hidden
type:basic:string
description:String 4 description.
out_group.string5
label:String 5 choices
type:basic:string
description:String 5 description.
out_group.string6
label:String 6 regex only “Aa”
type:basic:string
out_group.string7
label:String 7 optional choices
type:basic:string
out_tricky.tricky1.tricky2
label:Tricky 2
type:basic:string
Test disabled inputs
data:test:disabledtest-disabled (basic:boolean  broad, basic:integer  broad_width, basic:string  width_label, basic:integer  if_and_condition)[Source: v1.1.1]

Test disabled input fields.

Input arguments

broad
label:Broad peaks
type:basic:boolean
default:False
broad_width
label:Width of peaks
type:basic:integer
disabled:broad === false
default:5
width_label
label:Width label
type:basic:string
disabled:broad === false
default:FD
if_and_condition
label:If width is 5 and label FDR
type:basic:integer
disabled:broad_width == 5 && width_label == ‘FDR’
default:5

Output results

output
label:Result
type:basic:string
Test hidden inputs
data:test:hiddentest-hidden (basic:boolean  broad, basic:integer  broad_width, basic:integer  parameter1, basic:integer  parameter2, basic:integer  broad_width2)[Source: v1.1.1]

Test hidden input fields

Input arguments

broad
label:Broad peaks
type:basic:boolean
default:False
broad_width
label:Width of peaks
type:basic:integer
hidden:broad === false
default:5
parameters_broad_f.parameter1
label:parameter1
type:basic:integer
default:10
parameters_broad_f.parameter2
label:parameter2
type:basic:integer
default:10
parameters_broad_t.broad_width2
label:Width of peaks2
type:basic:integer
default:5

Output results

output
label:Result
type:basic:string
Test select controler
data:test:resulttest-list (data:test:result  single, list:data:test:result  multiple)[Source: v1.1.1]

Test with all basic input fields whose values are printed by the processor and returned unmodified as output fields.

Input arguments

single
label:Single
type:data:test:result
multiple
label:Multiple
type:list:data:test:result

Output results

output
label:Result
type:basic:string
Test sleep progress
data:test:resulttest-sleep-progress (basic:integer  t)[Source: v1.1.1]

Test for the progress bar by sleeping 5 times for the specified amount of time.

Input arguments

t
label:Sleep time
type:basic:integer
default:5

Output results

output
label:Result
type:basic:string
Trim, align and quantify using a library as a reference.
data:workflow:trimalquantworkflow-trim-align-quant (data:reads:fastq:single  reads, list:basic:string  up_primers_seq, list:basic:string  down_primers_seq, basic:decimal  error_rate_5end, basic:decimal  error_rate_3end, data:genome:fasta  genome, basic:string  mode, basic:integer  N, basic:integer  L, basic:integer  gbar, basic:string  mp, basic:string  rdg, basic:string  rfg, basic:string  score_min, basic:integer  readlengths, basic:integer  alignscores)[Source: v0.0.1]

Input arguments

reads
label:Untrimmed reads.
type:data:reads:fastq:single
description:First stage of shRNA pipeline. Trims 5’ adapters, then 3’ adapters using the same error rate setting, aligns reads to a reference library and quantifies species.
trimming_options.up_primers_seq
label:5’ adapter sequence
type:list:basic:string
description:A string of 5’ adapter sequence.
required:True
trimming_options.down_primers_seq
label:3’ adapter sequence
type:list:basic:string
description:A string of 3’ adapter sequence.
required:True
trimming_options.error_rate_5end
label:Error rate for 5’
type:basic:decimal
description:Maximum allowed error rate (no. of errors divided by the length of the matching region) for 5’ trimming.
required:False
default:0.1
trimming_options.error_rate_3end
label:Error rate for 3’
type:basic:decimal
description:Maximum allowed error rate (no. of errors divided by the length of the matching region) for 3’ trimming.
required:False
default:0.1
alignment_options.genome
label:Reference library
type:data:genome:fasta
description:Choose the reference library against which to align reads.
alignment_options.mode
label:Alignment mode
type:basic:string
description:End to end: Bowtie 2 requires that the entire read align from one end to the other, without any trimming (or “soft clipping”) of characters from either end. local: Bowtie 2 does not require that the entire read align from one end to the other. Rather, some characters may be omitted (“soft clipped”) from the ends in order to achieve the greatest possible alignment score.
default:--end-to-end
choices:
  • end to end mode: --end-to-end
  • local: --local
alignment_options.N
label:Number of mismatches allowed in seed alignment (N)
type:basic:integer
description:Sets the number of mismatches to allowed in a seed alignment during multiseed alignment. Can be set to 0 or 1. Setting this higher makes alignment slower (often much slower) but increases sensitivity. Default: 0.
required:False
alignment_options.L
label:Length of seed substrings (L)
type:basic:integer
description:Sets the length of the seed substrings to align during multiseed alignment. Smaller values make alignment slower but more sensitive. Default: the –sensitive preset is used by default for end-to-end alignment and –sensitive-local for local alignment. See documentation for details.
required:False
alignment_options.gbar
label:Disallow gaps within positions (gbar)
type:basic:integer
description:Disallow gaps within <int> positions of the beginning or end of the read. Default: 4.
required:False
alignment_options.mp
label:Maximal and minimal mismatch penalty (mp)
type:basic:string
description:Sets the maximum (MX) and minimum (MN) mismatch penalties, both integers. A number less than or equal to MX and greater than or equal to MN is subtracted from the alignment score for each position where a read character aligns to a reference character, the characters do not match, and neither is an N. If –ignore-quals is specified, the number subtracted quals MX. Otherwise, the number subtracted is MN + floor((MX-MN)(MIN(Q, 40.0)/40.0)) where Q is the Phred quality value. Default for MX, MN: 6,2.
required:False
alignment_options.rdg
label:Set read gap open and extend penalties (rdg)
type:basic:string
description:Sets the read gap open (<int1>) and extend (<int2>) penalties. A read gap of length N gets a penalty of <int1> + N * <int2>. Default: 5,3.
required:False
alignment_options.rfg
label:Set reference gap open and close penalties (rfg)
type:basic:string
description:Sets the reference gap open (<int1>) and extend (<int2>) penalties. A reference gap of length N gets a penalty of <int1> + N * <int2>. Default: 5,3.
required:False
alignment_options.score_min
label:Minimum alignment score needed for “valid” alignment (score-min)
type:basic:string
description:Sets a function governing the minimum alignment score needed for an alignment to be considered “valid” (i.e. good enough to report). This is a function of read length. For instance, specifying L,0,-0.6 sets the minimum-score function to f(x) = 0 + -0.6 * x, where x is the read length. The default in –end-to-end mode is L,-0.6,-0.6 and the default in –local mode is G,20,8.
required:False
quant_options.readlengths
label:Species lengths threshold
type:basic:integer
description:Species with read lengths below specified threshold will be removed from final output. Default is no removal.
quant_options.alignscores
label:Align scores filter threshold
type:basic:integer
description:Species with align score below specified threshold will be removed from final output. Default is no removal.

Output results

Trimmomatic (paired-end)
data:reads:fastq:paired:trimmomatictrimmomatic-paired (data:reads:fastq:paired  reads, data:seq:nucleotide  adapters, basic:integer  seed_mismatches, basic:integer  simple_clip_threshold, basic:integer  palindrome_clip_threshold, basic:integer  min_adapter_length, basic:boolean  keep_both_reads, basic:integer  window_size, basic:integer  required_quality, basic:integer  target_length, basic:decimal  strictness, basic:integer  leading, basic:integer  trailing, basic:integer  crop, basic:integer  headcrop, basic:integer  minlen, basic:integer  average_quality)[Source: v2.1.2]

Trimmomatic performs a variety of useful trimming tasks including removing adapters for Illumina paired-end and single-end data. FastQC is performed for quality control checks on trimmed raw sequence data, which are the output of Trimmomatic. See [Trimmomatic official website](http://www.usadellab.org/cms/?page=trimmomatic), the [introductory paper](https://www.ncbi.nlm.nih.gov/pubmed/24695404), and the [FastQC official website](https://www.bioinformatics.babraham.ac.uk/projects/fastqc/) for more information.

Input arguments

reads
label:Reads
type:data:reads:fastq:paired
illuminaclip.adapters
label:Adapter sequences
type:data:seq:nucleotide
description:Adapter sequence in FASTA format that will be removed from the read. This field as well as ‘Seed mismatches’, ‘Simple clip threshold’ and ‘Palindrome clip threshold’ parameters are needed to perform Illuminacliping. ‘Minimum adapter length’ and ‘Keep both reads’ are optional parameters.
required:False
illuminaclip.seed_mismatches
label:Seed mismatches
type:basic:integer
description:Specifies the maximum mismatch count which will still allow a full match to be performed. This field as well as ‘Adapter sequence’, ‘Simple clip threshold’ and ‘Palindrome clip threshold’ parameters are needed to perform Illuminacliping.
required:False
disabled:!illuminaclip.adapters
illuminaclip.simple_clip_threshold
label:Simple clip threshold
type:basic:integer
description:Specifies how accurate the match between any adapter etc. sequence must be against a read. This field as well as ‘Adapter sequence’, ‘Seed mismatches’ and ‘Palindrome clip threshold’ parameters are needed to perform Illuminacliping.
required:False
disabled:!illuminaclip.adapters
illuminaclip.palindrome_clip_threshold
label:Palindrome clip threshold
type:basic:integer
description:Specifies how accurate the match between the two ‘adapter ligated’ reads must be for PE palindrome read alignment. This field as well as ‘Adapter sequence’, ‘Simple clip threshold’ and ‘Seed mismatches’ parameters are needed to perform Illuminacliping.
required:False
disabled:!illuminaclip.adapters
illuminaclip.min_adapter_length
label:Minimum adapter length
type:basic:integer
description:In addition to the alignment score, palindrome mode can verify that a minimum length of adapter has been detected. If unspecified, this defaults to 8 bases, for historical reasons. However, since palindrome mode has a very low false positive rate, this can be safely reduced, even down to 1, to allow shorter adapter fragments to be removed. This field is optional for preforming Illuminaclip. ‘Adapter sequences’, ‘Seed mismatches’, ‘Simple clip threshold’ and ‘Palindrome clip threshold’ are also needed in order to use this parameter.
disabled:!illuminaclip.seed_mismatches && !illuminaclip.simple_clip_threshold && !illuminaclip.palindrome_clip_threshold
default:8
illuminaclip.keep_both_reads
label:Keep both reads
type:basic:boolean
description:After read-though has been detected by palindrome mode, and the adapter sequence removed, the reverse read contains the same sequence information as the forward read, albeit in reverse complement. For this reason, the default behaviour is to entirely drop the reverse read.By specifying this parameter, the reverse read will also be retained, which may be useful e.g. if the downstream tools cannot handle a combination of paired and unpaired reads. This field is optional for preforming Illuminaclip. ‘Adapter sequence’, ‘Seed mismatches’, ‘Simple clip threshold’, ‘Palindrome clip threshold’ and also ‘Minimum adapter length’ are needed in order to use this parameter.
required:False
disabled:!illuminaclip.seed_mismatches && !illuminaclip.simple_clip_threshold && !illuminaclip.palindrome_clip_threshold && !illuminaclip.min_adapter_length
slidingwindow.window_size
label:Window size
type:basic:integer
description:Specifies the number of bases to average across. This field as well as ‘Required quality’ are needed to perform a ‘Sliding window’ trimming (cutting once the average quality within the window falls below a threshold).
required:False
slidingwindow.required_quality
label:Required quality
type:basic:integer
description:Specifies the average quality required. This field as well as ‘Window size’ are needed to perform a ‘Sliding window’ trimming (cutting once the average quality within the window falls below a threshold).
required:False
maxinfo.target_length
label:Target length
type:basic:integer
description:This specifies the read length which is likely to allow the location of the read within the target sequence to be determined. This field as well as ‘Strictness’ are needed to perform ‘Maxinfo’ feature (an adaptive quality trimmer which balances read length and error rate to maximise the value of each read).
required:False
maxinfo.strictness
label:Strictness
type:basic:decimal
description:This value, which should be set between 0 and 1, specifies the balance between preserving as much read length as possible vs. removal of incorrect bases. A low value of this parameter (<0.2) favours longer reads, while a high value (>0.8) favours read correctness. This field as well as ‘Target length’ are needed to perform ‘Maxinfo’ feature (an adaptive quality trimmer which balances read length and error rate to maximise the value of each read).
required:False
trim_bases.leading
label:Leading quality
type:basic:integer
description:Remove low quality bases from the beginning. Specifies the minimum quality required to keep a base.
required:False
trim_bases.trailing
label:Trailing
type:basic:integer
description:Remove low quality bases from the end. Specifies the minimum quality required to keep a base.
required:False
trim_bases.crop
label:Crop
type:basic:integer
description:Cut the read to a specified length by removing bases from the end.
required:False
trim_bases.headcrop
label:Headcrop
type:basic:integer
description:Cut the specified number of bases from the start of the read.
required:False
reads_filtering.minlen
label:Minimum length
type:basic:integer
description:Drop the read if it is below a specified length.
required:False
reads_filtering.average_quality
label:Average quality
type:basic:integer
description:Drop the read if the average quality is below the specified level.
required:False

Output results

fastq
label:Reads file (mate 1)
type:list:basic:file
fastq_unpaired
label:Reads file
type:basic:file
required:False
fastq2
label:Reads file (mate 2)
type:list:basic:file
fastq2_unpaired
label:Reads file
type:basic:file
required:False
fastqc_url
label:Quality control with FastQC (Upstream)
type:list:basic:file:html
fastqc_url2
label:Quality control with FastQC (Downstream)
type:list:basic:file:html
fastqc_archive
label:Download FastQC archive (Upstream)
type:list:basic:file
fastqc_archive2
label:Download FastQC archive (Downstream)
type:list:basic:file
Trimmomatic (single-end)
data:reads:fastq:single:trimmomatictrimmomatic-single (data:reads:fastq:single  reads, data:seq:nucleotide  adapters, basic:integer  seed_mismatches, basic:integer  simple_clip_threshold, basic:integer  window_size, basic:integer  required_quality, basic:integer  target_length, basic:decimal  strictness, basic:integer  leading, basic:integer  trailing, basic:integer  crop, basic:integer  headcrop, basic:integer  minlen, basic:integer  average_quality)[Source: v2.1.2]

Trimmomatic performs a variety of useful trimming tasks including removing adapters for Illumina paired-end and single-end data. FastQC is performed for quality control checks on trimmed raw sequence data, which are the output of Trimmomatic. See [Trimmomatic official website](http://www.usadellab.org/cms/?page=trimmomatic), the [introductory paper](https://www.ncbi.nlm.nih.gov/pubmed/24695404), and the [FastQC official website](https://www.bioinformatics.babraham.ac.uk/projects/fastqc/) for more information.

Input arguments

reads
label:Reads
type:data:reads:fastq:single
illuminaclip.adapters
label:Adapter sequences
type:data:seq:nucleotide
description:Adapter sequence in FASTA format that will be removed from the read. This field as well as ‘Seed mismatches’ and ‘Simple clip threshold’ parameters are needed to perform Illuminacliping.
required:False
illuminaclip.seed_mismatches
label:Seed mismatches
type:basic:integer
description:Specifies the maximum mismatch count which will still allow a full match to be performed. This field as well as ‘Adapter sequences’ and ‘Simple clip threshold’ parameter are needed to perform Illuminacliping.
required:False
disabled:!illuminaclip.adapters
illuminaclip.simple_clip_threshold
label:Simple clip threshold
type:basic:integer
description:Specifies how accurate the match between any adapter etc. sequence must be against a read. This field as well as ‘Adapter sequences’ and ‘Seed mismatches’ parameter are needed to perform Illuminacliping.
required:False
disabled:!illuminaclip.adapters
slidingwindow.window_size
label:Window size
type:basic:integer
description:Specifies the number of bases to average across. This field as well as ‘Required quality’ are needed to perform a ‘Sliding window’ trimming (cutting once the average quality within the window falls below a threshold).
required:False
slidingwindow.required_quality
label:Required quality
type:basic:integer
description:Specifies the average quality required in window size. This field as well as ‘Window size’ are needed to perform a ‘Sliding window’ trimming (cutting once the average quality within the window falls below a threshold).
required:False
maxinfo.target_length
label:Target length
type:basic:integer
description:This specifies the read length which is likely to allow the location of the read within the target sequence to be determined. This field as well as ‘Strictness’ are needed to perform ‘Maxinfo’ feature (an adaptive quality trimmer which balances read length and error rate to maximise the value of each read).
required:False
maxinfo.strictness
label:Strictness
type:basic:decimal
description:This value, which should be set between 0 and 1, specifies the balance between preserving as much read length as possible vs. removal of incorrect bases. A low value of this parameter (<0.2) favours longer reads, while a high value (>0.8) favours read correctness. This field as well as ‘Target length’ are needed to perform ‘Maxinfo’ feature (an adaptive quality trimmer which balances read length and error rate to maximise the value of each read).
required:False
trim_bases.leading
label:Leading quality
type:basic:integer
description:Remove low quality bases from the beginning, if below a threshold quality.
required:False
trim_bases.trailing
label:Trailing quality
type:basic:integer
description:Remove low quality bases from the end, if below a threshold quality.
required:False
trim_bases.crop
label:Crop
type:basic:integer
description:Cut the read to a specified length by removing bases from the end.
required:False
trim_bases.headcrop
label:Headcrop
type:basic:integer
description:Cut the specified number of bases from the start of the read.
required:False
reads_filtering.minlen
label:Minimum length
type:basic:integer
description:Drop the read if it is below a specified length.
required:False
reads_filtering.average_quality
label:Average quality
type:basic:integer
description:Drop the read if the average quality is below the specified level.
required:False

Output results

fastq
label:Reads file
type:list:basic:file
fastqc_url
label:Quality control with FastQC
type:list:basic:file:html
fastqc_archive
label:Download FastQC archive
type:list:basic:file
Trimmomatic - HISAT2 - HTSeq-count (paired-end)
data:workflow:rnaseq:htseqworkflow-rnaseq-paired (data:reads:fastq:paired  reads, data:genome:fasta  genome, data:annotation:gtf  annotation, data:seq:nucleotide  adapters, basic:integer  seed_mismatches, basic:integer  palindrome_clip_threshold, basic:integer  simple_clip_threshold, basic:integer  minlen, basic:integer  trailing, basic:string  stranded, basic:string  id_attribute)[Source: v1.0.1]

This RNA-seq pipeline is comprised of three steps, preprocessing, alignment, and quantification. First, reads are preprocessed by __Trimmomatic__ which performs a variety of useful trimming tasks including removing adapters for Illumina paired-end and single-end high-throughput sequencing reads. Next, preprocessed reads are aligned by __HISAT2__ aligner. HISAT2 is a fast and sensitive alignment program for mapping next-generation sequencing reads For more information see [this comparison of RNA-seq aligners](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5792058/). Finally, aligned reads are summarized to genes by __HTSeq-count__. Compared to featureCounts, HTSeq-count is not as computationally efficient. All three tools in this workflow support parallelization to accelerate the analysis.

Input arguments

reads
label:Input reads
type:data:reads:fastq:paired
genome
label:Genome
type:data:genome:fasta
annotation
label:Annotation (GTF)
type:data:annotation:gtf
adapters
label:Adapter sequences (FASTA)
type:data:seq:nucleotide
required:False
illuminaclip.seed_mismatches
label:Seed mismatches
type:basic:integer
description:Specifies the maximum mismatch count which will still allow a full match to be performed.
default:2
illuminaclip.palindrome_clip_threshold
label:Palindrome clip threshold
type:basic:integer
description:Specifies how accurate the match between the two ‘adapter ligated’ reads must be for PE palindrome read alignment.
default:30
illuminaclip.simple_clip_threshold
label:Simple clip threshold
type:basic:integer
description:Specifies how accurate the match between any adapter etc. sequence must be against a read.
default:10
minlen
label:Min length
type:basic:integer
description:Drop the read if it is below a specified length.
default:10
trailing
label:Trailing quality
type:basic:integer
description:Remove low quality bases from the end. Specifies the minimum quality required to keep a base.
default:28
stranded
label:Is data from a strand specific assay?
type:basic:string
description:In strand non-specific assay a read is considered overlapping with a feature regardless of whether it is mapped to the same or the opposite strand as the feature. In strand-specific forward assay and single reads, the read has to be mapped to the same strand as the feature. For paired-end reads, the first read has to be on the same strand and the second read on the opposite strand. In strand-specific reverse assay these rules are reversed.
default:no
choices:
  • Strand non-specific: no
  • Strand-specific forward: yes
  • Strand-specific reverse: reverse
id_attribute
label:ID attribute
type:basic:string
description:GFF attribute to be used as feature ID. Several GFF lines with the same feature ID will be considered as parts of the same feature. The feature ID is used to identity the counts in the output table.
default:gene_id

Output results

Trimmomatic - HISAT2 - HTSeq-count (single-end)
data:workflow:rnaseq:htseqworkflow-rnaseq-single (data:reads:fastq:single  reads, data:genome:fasta  genome, data:annotation:gtf  annotation, data:seq:nucleotide  adapters, basic:integer  seed_mismatches, basic:integer  simple_clip_threshold, basic:integer  minlen, basic:integer  trailing, basic:string  stranded, basic:string  id_attribute)[Source: v1.0.1]

This RNA-seq pipeline is comprised of three steps, preprocessing, alignment, and quantification. First, reads are preprocessed by __Trimmomatic__ which performs a variety of useful trimming tasks including removing adapters for Illumina paired-end and single-end high-throughput sequencing reads. Next, preprocessed reads are aligned by __HISAT2__ aligner. HISAT2 is a fast and sensitive alignment program for mapping next-generation sequencing reads For more information see [this comparison of RNA-seq aligners](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5792058/). Finally, aligned reads are summarized to genes by __HTSeq-count__. Compared to featureCounts, HTSeq-count is not as computationally efficient. All three tools in this workflow support parallelization to accelerate the analysis.

Input arguments

reads
label:Input reads
type:data:reads:fastq:single
genome
label:Genome
type:data:genome:fasta
annotation
label:Annotation (GTF)
type:data:annotation:gtf
adapters
label:Adapter sequences (FASTA)
type:data:seq:nucleotide
required:False
illuminaclip.seed_mismatches
label:Seed mismatches
type:basic:integer
description:Specifies the maximum mismatch count which will still allow a full match to be performed.
default:2
illuminaclip.simple_clip_threshold
label:Simple clip threshold
type:basic:integer
description:Specifies how accurate the match between any adapter etc. sequence must be against a read.
default:10
minlen
label:Minimum length
type:basic:integer
description:Drop the read if it is below a specified length.
default:10
trailing
label:Trailing quality
type:basic:integer
description:Remove low quality bases from the end. Specifies the minimum quality required to keep a base.
default:28
stranded
label:Is data from a strand specific assay?
type:basic:string
description:In strand non-specific assay a read is considered overlapping with a feature regardless of whether it is mapped to the same or the opposite strand as the feature. In strand-specific forward assay and single reads, the read has to be mapped to the same strand as the feature. For paired-end reads, the first read has to be on the same strand and the second read on the opposite strand. In strand-specific reverse assay these rules are reversed.
default:no
choices:
  • Strand non-specific: no
  • Strand-specific forward: yes
  • Strand-specific reverse: reverse
id_attribute
label:ID attribute
type:basic:string
description:GFF attribute to be used as feature ID. Several GFF lines with the same feature ID will be considered as parts of the same feature. The feature ID is used to identity the counts in the output table.
default:gene_id

Output results

Upload Picard CollectTargetedPcrMetrics
data:picard:coverage:uploadupload-picard-pcrmetrics (basic:file  target_pcr_metrics, basic:file  target_coverage)[Source: v1.1.1]

Upload Picard CollectTargetedPcrMetrics result files.

Input arguments

target_pcr_metrics
label:Target PCR metrics
type:basic:file
target_coverage
label:Target coverage
type:basic:file

Output results

target_pcr_metrics
label:Target PCR metrics
type:basic:file
target_coverage
label:Target coverage
type:basic:file
VCF file
data:variants:vcfupload-variants-vcf (basic:file  src, basic:string  species, basic:string  build)[Source: v2.1.1]

Upload variants in VCF format.

Input arguments

src
label:Variants (VCF)
type:basic:file
description:Variants in VCF format.
required:True
validate_regex:\.(vcf)(|\.gz|\.bz2|\.tgz|\.tar\.gz|\.tar\.bz2|\.zip|\.rar|\.7z)$
species
label:Species
type:basic:string
description:Species latin name.
choices:
  • Homo sapiens: Homo sapiens
  • Mus musculus: Mus musculus
  • Rattus norvegicus: Rattus norvegicus
  • Dictyostelium discoideum: Dictyostelium discoideum
  • Odocoileus virginianus texanus: Odocoileus virginianus texanus
  • Solanum tuberosum: Solanum tuberosum
build
label:Genome build
type:basic:string

Output results

vcf
label:Uploaded file
type:basic:file
tbi
label:Tabix index
type:basic:file
species
label:Species
type:basic:string
build
label:Build
type:basic:string
Variant calling (CheMut)
data:variants:vcf:chemutvc-chemut (data:genome:fasta  genome, list:data:alignment:bam  parental_strains, list:data:alignment:bam  mutant_strains, basic:boolean  br_and_ind_ra, basic:boolean  dbsnp, data:variants:vcf  known_sites, list:data:variants:vcf  known_indels, basic:string  PL, basic:string  LB, basic:string  PU, basic:string  CN, basic:date  DT, basic:integer  stand_emit_conf, basic:integer  stand_call_conf, basic:integer  ploidy, basic:string  glm, list:basic:string  intervals, basic:boolean  rf)[Source: v1.2.2]

“CheMut varint calling using multiple BAM input files. Note: Usage of Genome Analysis Toolkit requires a licence.”

Input arguments

genome
label:Reference genome
type:data:genome:fasta
parental_strains
label:Parental strains
type:list:data:alignment:bam
mutant_strains
label:Mutant strains
type:list:data:alignment:bam
br_and_ind_ra
label:Do variant base recalibration and indel realignment
type:basic:boolean
default:False
dbsnp
label:Use dbSNP file
type:basic:boolean
description:rsIDs from this file are used to populate the ID column of the output. Also, the DB INFO flag will be set when appropriate. dbSNP is not used in any way for the calculations themselves.
default:False
known_sites
label:Known sites (dbSNP)
type:data:variants:vcf
required:False
hidden:br_and_ind_ra === false && dbsnp === false
known_indels
label:Known indels
type:list:data:variants:vcf
required:False
hidden:br_and_ind_ra === false
reads_info.PL
label:Platform/technology
type:basic:string
description:Platform/technology used to produce the reads.
default:Illumina
choices:
  • Capillary: Capillary
  • Ls454: Ls454
  • Illumina: Illumina
  • SOLiD: SOLiD
  • Helicos: Helicos
  • IonTorrent: IonTorrent
  • Pacbio: Pacbio
reads_info.LB
label:Library
type:basic:string
default:x
reads_info.PU
label:Platform unit
type:basic:string
description:Platform unit (e.g. flowcell-barcode.lane for Illumina or slide for SOLiD). Unique identifier.
default:x
reads_info.CN
label:Sequencing center
type:basic:string
description:Name of sequencing center producing the read.
default:x
reads_info.DT
label:Date
type:basic:date
description:Date the run was produced.
default:2017-01-01
Varc_param.stand_emit_conf
label:Emission confidence threshold
type:basic:integer
description:The minimum confidence threshold (phred-scaled) at which the program should emit sites that appear to be possibly variant.
default:10
Varc_param.stand_call_conf
label:Calling confidence threshold
type:basic:integer
description:The minimum confidence threshold (phred-scaled) at which the program should emit variant sites as called. If a site’s associated genotype has a confidence score lower than the calling threshold, the program will emit the site as filtered and will annotate it as LowQual. This threshold separates high confidence calls from low confidence calls.
default:30
Varc_param.ploidy
label:Sample ploidy
type:basic:integer
description:Ploidy (number of chromosomes) per sample. For pooled data, set to (Number of samples in each pool * Sample Ploidy).
default:2
Varc_param.glm
label:Genotype likelihoods model
type:basic:string
description:Genotype likelihoods calculation model to employ – SNP is the default option, while INDEL is also available for calling indels and BOTH is available for calling both together.
default:SNP
choices:
  • SNP: SNP
  • INDEL: INDEL
  • BOTH: BOTH
Varc_param.intervals
label:Intervals
type:list:basic:string
description:Use this option to perform the analysis over only part of the genome. This argument can be specified multiple times. You can use samtools-style intervals (e.g. -L chr1 or -L chr1:100-200).
required:False
Varc_param.rf
label:ReasignOneMappingQuality Filter
type:basic:boolean
description:This read transformer will change a certain read mapping quality to a different value without affecting reads that have other mapping qualities. This is intended primarily for users of RNA-Seq data handling programs such as TopHat, which use MAPQ = 255 to designate uniquely aligned reads. According to convention, 255 normally designates “unknown” quality, and most GATK tools automatically ignore such reads. By reassigning a different mapping quality to those specific reads, users of TopHat and other tools can circumvent this problem without affecting the rest of their dataset.
default:False

Output results

vcf
label:Called variants file
type:basic:file
tbi
label:Tabix index
type:basic:file
species
label:Species
type:basic:string
build
label:Build
type:basic:string
Variant filtering (CheMut)
data:variants:vcf:filteringfiltering-chemut (data:variants:vcf  variants, basic:string  analysis_type, basic:string  parental_strain, basic:string  mutant_strain, basic:integer  read_depth)[Source: v1.3.1]

Filtering and annotation of Variant Calling data - Chemical mutagenesis in Dictyostelium discoideum

Input arguments

variants
label:Variants file (VCF)
type:data:variants:vcf
analysis_type
label:Analysis type
type:basic:string
description:Choice of the analysis type. Use “SNV” or “INDEL” options for the analysis of haploid VCF files prepared by using GATK UnifiedGenotyper -glm option “SNP” or “INDEL”, respectively. Choose options SNV_CHR2 or INDEL_CHR2 to run the GATK analysis only on the diploid portion of CHR2 (-ploidy 2 -L chr2:2263132-3015703).
default:snv
choices:
  • SNV: snv
  • INDEL: indel
  • SNV_CHR2: snv_chr2
  • INDEL_CHR2: indel_chr2
parental_strain
label:Parental Strain Prefix
type:basic:string
default:parental
mutant_strain
label:Mutant Strain Prefix
type:basic:string
default:mut
read_depth
label:Read Depth Cutoff
type:basic:integer
default:5

Output results

summary
label:Summary
type:basic:file
description:Summarize the input parameters and results.
vcf
label:Variants
type:basic:file
description:A genome VCF file of variants that passed the filters.
tbi
label:Tabix index
type:basic:file
variants_filtered
label:Variants filtered
type:basic:file
description:A data frame of variants that passed the filters.
required:False
variants_filtered_alt
label:Variants filtered (multiple alt. alleles)
type:basic:file
description:A data frame of variants that contain more than two alternative alleles. These vairants are likely to be false positives.
required:False
gene_list_all
label:Gene list (all)
type:basic:file
description:Genes that are mutated at least once.
required:False
gene_list_top
label:Gene list (top)
type:basic:file
description:Genes that are mutated at least twice.
required:False
mut_chr
label:Mutations (by chr)
type:basic:file
description:List mutations in individual chromosomes.
required:False
mut_strain
label:Mutations (by strain)
type:basic:file
description:List mutations in individual strains.
required:False
strain_by_gene
label:Strain (by gene)
type:basic:file
description:List mutants that carry mutations in individual genes.
required:False
species
label:Species
type:basic:string
build
label:Build
type:basic:string
WALT
data:alignment:mr:waltwalt (data:genome:fasta  genome, data:reads:fastq  reads, basic:boolean  rm_dup, basic:integer  mismatch, basic:integer  number)[Source: v1.0.2]

WALT (Wildcard ALignment Tool) is a read mapping program for bisulfite sequencing in DNA methylation studies.

Input arguments

genome
label:Reference genome
type:data:genome:fasta
reads
label:Reads
type:data:reads:fastq
rm_dup
label:Remove duplicates
type:basic:boolean
default:True
mismatch
label:Maximum allowed mismatches
type:basic:integer
required:False
number
label:Number of reads to map in one loop
type:basic:integer
description:Sets the number of reads to mapping in each loop. Larger number results in program taking more memory. This is especially evident in paired-end mapping.
required:False

Output results

mr
label:Alignment file
type:basic:file
description:Position sorted alignment
stats
label:Statistics
type:basic:file
unmapped_f
label:Unmapped reads (mate 1)
type:basic:file
required:False
unmapped_r
label:Unmapped reads (mate 2)
type:basic:file
required:False
species
label:Species
type:basic:string
build
label:Build
type:basic:string
WGBS
data:workflow:wgbsworkflow-wgbs (data:reads:fastq  reads, data:genome:fasta  genome, basic:boolean  rm_dup, basic:integer  mismatch, basic:integer  number, basic:boolean  cpgs, basic:boolean  symmetric_cpgs)[Source: v1.0.2]

This WGBS pipeline is comprised of three steps - alignment, computation of methylation levels, and identification of hypo-methylated regions (HMRs). First, reads are aligned by __WALT__ aligner. [WALT (Wildcard ALignment Tool)](https://github.com/smithlabcode/walt) is fast and accurate read mapping for bisulfite sequencing. Then, methylation level at each genomic cytosine is calculated using __methcounts__. Finally, hypo-methylated regions are identified using __hmr__. Both methcounts and hmr are part of [MethPipe](http://smithlabresearch.org/software/methpipe/) package.

Input arguments

reads
label:Select sample(s)
type:data:reads:fastq
genome
label:Genome
type:data:genome:fasta
alignment.rm_dup
label:Remove duplicates
type:basic:boolean
default:True
alignment.mismatch
label:Maximum allowed mismatches
type:basic:integer
default:6
alignment.number
label:Number of reads to map in one loop
type:basic:integer
description:Sets the number of reads to mapping in each loop. Larger number results in program taking more memory. This is especially evident in paired-end mapping.
required:False
methcounts.cpgs
label:Only CpG context sites
type:basic:boolean
description:Output file will contain methylation data for CpG context sites only. Choosing this option will result in CpG content report only.
disabled:methcounts.symmetric_cpgs
default:False
methcounts.symmetric_cpgs
label:Merge CpG pairs
type:basic:boolean
description:Merging CpG pairs results in symmetric methylation levels. Methylation is usually symmetric (cytosines at CpG sites were methylated on both DNA strands). Choosing this option will only keep the CpG sites data.
disabled:methcounts.cpgs
default:True

Output results

Whole exome sequencing (WES) analysis
data:workflow:wesworkflow-wes (data:reads:fastq:paired  reads, data:genome:fasta  genome, data:bedpe  bamclipper_bedpe, list:data:variants:vcf  known_sites, data:bed  intervals, data:variants:vcf  hc_dbsnp, basic:string  validation_stringency, data:seq:nucleotide  adapters, basic:integer  seed_mismatches, basic:integer  simple_clip_threshold, basic:integer  min_adapter_length, basic:integer  palindrome_clip_threshold, basic:integer  leading, basic:integer  trailing, basic:integer  minlen, basic:integer  seed_l, basic:integer  band_w, basic:boolean  m, basic:decimal  re_seeding, basic:integer  match, basic:integer  mismatch, basic:integer  gap_o, basic:integer  gap_e, basic:integer  clipping, basic:integer  unpaired_p, basic:integer  report_tr, basic:boolean  md_skip, basic:boolean  md_remove_duplicates, basic:string  md_assume_sort_order, basic:string  read_group, basic:integer  stand_call_conf, basic:integer  mbq)[Source: v2.0.0]

Whole exome sequencing pipeline analyzes Illumina panel data. It consists of trimming, aligning, soft clipping, (optional) marking of duplicates, recalibration of base quality scores and finally, calling of variants. The tools used are Trimmomatic which performs trimming. Aligning is performed using BWA (mem). Soft clipping of Illumina primer sequences is done using bamclipper tool. Marking of duplicates (MarkDuplicates), recalibration of base quality scores (ApplyBQSR) and calling of variants (HaplotypeCaller) is done using GATK4 bundle of bioinformatics tools. To successfully run this pipeline, you will need a genome (FASTA), paired-end (FASTQ) files, BEDPE file for bamclipper, known sites of variation (dbSNP) (VCF), dbSNP database of variations (can be the same as known sites of variation), intervals on which target capture was done (BED) and illumina adapter sequences (FASTA). Make sure that specified resources match the genome used in the alignment step. Result is a file of called variants (VCF).

Input arguments

reads
label:Raw untrimmed reads
type:data:reads:fastq:paired
description:Raw paired-end reads.
required:True
genome
label:Reference genome
type:data:genome:fasta
description:Against which genome to align. Further processes depend on this genome (e.g. BQSR step).
required:True
bamclipper_bedpe
label:BEDPE file used for clipping using Bamclipper
type:data:bedpe
description:BEDPE file used for clipping using Bamclipper tool.
required:True
known_sites
label:Known sites of variation used in BQSR
type:list:data:variants:vcf
description:Known sites of variation as a VCF file.
required:True
intervals
label:Intervals
type:data:bed
description:Use intervals to narrow the analysis to defined regions. This usually help cutting down on process time.
required:True
hc_dbsnp
label:dbSNP for GATK4’s HaplotypeCaller
type:data:variants:vcf
description:dbSNP database of variants for variant calling.
required:True
validation_stringency
label:Validation stringency for all SAM files read by this program. Setting stringency to SILENT can improve performance when processing a BAM file in which variable-length data (read, qualities, tags) do not otherwise need to be decoded. Default is STRICT. This setting is used in BaseRecalibrator and ApplyBQSR processes.
type:basic:string
default:STRICT
choices:
  • STRICT: STRICT
  • SILENT: SILENT
  • LENIENT: LENIENT
advanced.trimming.adapters
label:Adapter sequences
type:data:seq:nucleotide
description:Adapter sequence in FASTA format that will be removed from the read. This field as well as ‘Seed mismatches’, ‘Simple clip threshold’ and ‘Palindrome clip threshold’ parameters are needed to perform Illuminacliping. ‘Minimum adapter length’ and ‘Keep both reads’ are optional parameters.
required:False
advanced.trimming.seed_mismatches
label:Seed mismatches
type:basic:integer
description:Specifies the maximum mismatch count which will still allow a full match to be performed. This field as well as ‘Adapter sequence’, ‘Simple clip threshold’ and ‘Palindrome clip threshold’ parameters are needed to perform Illuminacliping.
required:False
disabled:!advanced.trimming.adapters
advanced.trimming.simple_clip_threshold
label:Simple clip threshold
type:basic:integer
description:Specifies how accurate the match between any adapter etc. sequence must be against a read. This field as well as ‘Adapter sequences’ and ‘Seed mismatches’ parameter are needed to perform Illuminacliping.
required:False
disabled:!advanced.trimming.adapters
advanced.trimming.min_adapter_length
label:Minimum adapter length
type:basic:integer
description:In addition to the alignment score, palindrome mode can verify that a minimum length of adapter has been detected. If unspecified, this defaults to 8 bases, for historical reasons. However, since palindrome mode has a very low false positive rate, this can be safely reduced, even down to 1, to allow shorter adapter fragments to be removed. This field is optional for preforming Illuminaclip. ‘Adapter sequences’, ‘Seed mismatches’, ‘Simple clip threshold’ and ‘Palindrome clip threshold’ are also needed in order to use this parameter.
disabled:!advanced.trimming.seed_mismatches && !advanced.trimming.simple_clip_threshold && !advanced.trimming.palindrome_clip_threshold
default:8
advanced.trimming.palindrome_clip_threshold
label:Palindrome clip threshold
type:basic:integer
description:Specifies how accurate the match between the two ‘adapter ligated’ reads must be for PE palindrome read alignment. This field as well as ‘Adapter sequence’, ‘Simple clip threshold’ and ‘Seed mismatches’ parameters are needed to perform Illuminaclipping.
required:False
disabled:!advanced.trimming.adapters
advanced.trimming.leading
label:Leading quality
type:basic:integer
description:Remove low quality bases from the beginning, if below a threshold quality.
required:False
advanced.trimming.trailing
label:Trailing quality
type:basic:integer
description:Remove low quality bases from the end, if below a threshold quality.
required:False
advanced.trimming.minlen
label:Minimum length
type:basic:integer
description:Drop the read if it is below a specified length.
required:False
advanced.align.seed_l
label:Minimum seed length
type:basic:integer
description:Minimum seed length. Matches shorter than minimum seed length will be missed. The alignment speed is usually insensitive to this value unless it significantly deviates 20.
default:19
advanced.align.band_w
label:Band width
type:basic:integer
description:Gaps longer than this will not be found.
default:100
advanced.align.m
label:Mark shorter split hits as secondary
type:basic:boolean
description:Mark shorter split hits as secondary (for Picard compatibility)
default:False
advanced.align.re_seeding
label:Re-seeding factor
type:basic:decimal
description:Trigger re-seeding for a MEM longer than minSeedLen*FACTOR. This is a key heuristic parameter for tuning the performance. Larger value yields fewer seeds, which leads to faster alignment speed but lower accuracy.
default:1.5
advanced.align.scoring.match
label:Score of a match
type:basic:integer
default:1
advanced.align.scoring.mismatch
label:Mismatch penalty
type:basic:integer
default:4
advanced.align.scoring.gap_o
label:Gap open penalty
type:basic:integer
default:6
advanced.align.scoring.gap_e
label:Gap extension penalty
type:basic:integer
default:1
advanced.align.scoring.clipping
label:Clipping penalty
type:basic:integer
description:Clipping is applied if final alignment score is smaller than (best score reaching the end of query) - (Clipping penalty)
default:5
advanced.align.scoring.unpaired_p
label:Penalty for an unpaired read pair
type:basic:integer
description:Affinity to force pair. Score: scoreRead1+scoreRead2-Penalty
default:9
advanced.align.report_tr
label:Report threshold score
type:basic:integer
description:Don’t output alignment with score lower than defined number. This option only affects output.
default:30
advanced.markduplicates.md_skip
label:Skip GATK’s MarkDuplicates step
type:basic:boolean
default:False
advanced.markduplicates.md_remove_duplicates
label:Remove found duplicates
type:basic:boolean
default:False
advanced.markduplicates.md_assume_sort_order
label:Assume sort oder
type:basic:string
default:
choices:
  • as in BAM header (default):
  • unsorted: unsorted
  • queryname: queryname
  • coordinate: coordinate
  • duplicate: duplicate
  • unknown: unknown
advanced.bqsr.read_group
label:Read group (@RG)
type:basic:string
description:If BAM file has not been prepared using a @RG tag, you can add it here. This argument enables the user to replace all read groups in the INPUT file with a single new read group and assign all reads to this read group in the OUTPUT BAM file. Addition or replacement is performed using Picard’s AddOrReplaceReadGroups tool. Input should take the form of -name=value delimited by a \t, e.g. “-ID=1\t-PL=Illumina\t-SM=sample_1”. See AddOrReplaceReadGroups documentation for more information on tag names. Note that PL, LB, PU and SM are required fields. See caveats of rewriting read groups in the documentation linked above.
required:False
advanced.hc.stand_call_conf
label:Min call confidence threshold
type:basic:integer
description:The minimum phred-scaled confidence threshold at which variants should be called.
default:20
advanced.hc.mbq
label:Min Base Quality
type:basic:integer
description:Minimum base quality required to consider a base for calling.
default:20

Output results

coverageBed
data:coveragecoveragebed (data:alignment:bam  alignment, data:masterfile:amplicon  master_file)[Source: v4.1.1]

Bedtools coverage (coveragebed)

Input arguments

alignment
label:Alignment (BAM)
type:data:alignment:bam
master_file
label:Master file
type:data:masterfile:amplicon

Output results

cov_metrics
label:Coverage metrics
type:basic:file
mean_cov
label:Mean amplicon coverage
type:basic:file
amplicon_cov
label:Amplicon coverage file (nomergebed)
type:basic:file
covplot_html
label:HTML coverage plot
type:basic:file:html
edgeR
data:differentialexpression:edgerdifferentialexpression-edger (list:data:expression  case, list:data:expression  control, basic:integer  filter)[Source: v1.1.1]

Empirical Analysis of Digital Gene Expression Data in R (edgeR). Differential expression analysis of RNA-seq expression profiles with biological replication. Implements a range of statistical methodology based on the negative binomial distributions, including empirical Bayes estimation, exact tests, generalized linear models and quasi-likelihood tests. As well as RNA-seq, it be applied to differential signal analysis of other types of genomic data that produce counts, including ChIP-seq, Bisulfite-seq, SAGE and CAGE. See [here](https://www.bioconductor.org/packages/devel/bioc/vignettes/edgeR/inst/doc/edgeRUsersGuide.pdf) for more information.

Input arguments

case
label:Case
type:list:data:expression
description:Case samples (replicates)
control
label:Control
type:list:data:expression
description:Control samples (replicates)
filter
label:Raw counts filtering threshold
type:basic:integer
description:Filter genes in the expression matrix input. Remove genes where the number of counts in all samples is below the threshold.
default:10

Output results

raw
label:Differential expression
type:basic:file
de_json
label:Results table (JSON)
type:basic:json
de_file
label:Results table (file)
type:basic:file
source
label:Gene ID database
type:basic:string
species
label:Species
type:basic:string
build
label:Build
type:basic:string
feature_type
label:Feature type
type:basic:string
featureCounts
data:expression:featurecountsfeature_counts (data:alignment:bam  aligned_reads, basic:string  assay_type, data:index:salmon  cdna_index, basic:integer  n_reads, data:annotation  annotation, basic:string  feature_class, basic:string  feature_type, basic:string  id_attribute, basic:string  normalization_type, data:mappability:bcm  mappability, basic:boolean  show_advanced, basic:boolean  count_features, basic:boolean  allow_multi_overlap, basic:integer  min_overlap, basic:decimal  frac_overlap, basic:decimal  frac_overlap_feature, basic:boolean  largest_overlap, basic:integer  read_extension_5, basic:integer  read_extension_3, basic:integer  read_to_pos, basic:boolean  count_multi_mapping_reads, basic:boolean  fraction, basic:integer  min_mqs, basic:boolean  split_only, basic:boolean  non_split_only, basic:boolean  primary, basic:boolean  ignore_dup, basic:boolean  junc_counts, data:genome  genome, basic:boolean  is_paired_end, basic:boolean  require_both_ends_mapped, basic:boolean  check_frag_length, basic:integer  min_frag_length, basic:integer  max_frag_length, basic:boolean  do_not_count_chimeric_fragments, basic:boolean  do_not_sort, basic:boolean  by_read_group, basic:boolean  count_long_reads, basic:boolean  report_reads, basic:integer  max_mop, basic:boolean  verbose)[Source: v2.4.1]

featureCounts is a highly efficient general-purpose read summarization program that counts mapped reads for genomic features such as genes, exons, promoter, gene bodies, genomic bins and chromosomal locations. It can be used to count both RNA-seq and genomic DNA-seq reads. See the [official website](http://bioinf.wehi.edu.au/featureCounts/) and the [introductory paper](https://academic.oup.com/bioinformatics/article/30/7/923/232889) for more information.

Input arguments

alignment.aligned_reads
label:Aligned reads
type:data:alignment:bam
alignment.assay_type
label:Assay type
type:basic:string
description:Indicate if strand-specific read counting should be performed. For paired-end reads, strand of the first read is taken as the strand of the whole fragment. FLAG field is used to tell if a read is first or second read in a pair. Automated strand detection is enabled using the [Salmon](https://salmon.readthedocs.io/en/latest/library_type.html) tool’s build-in functionality. To use this option, cDNA (transcriptome) index file crated using the Salmon indexing tool must be provided.
default:non_specific
choices:
  • Strand non-specific: non_specific
  • Strand-specific forward: forward
  • Strand-specific reverse: reverse
  • Detect automatically: auto
alignment.cdna_index
label:cDNA index file
type:data:index:salmon
description:Transcriptome index file created using the Salmon indexing tool. cDNA (transcriptome) sequences used for index file creation must be derived from the same species as the input sequencing reads to obtain the reliable analysis results.
required:False
hidden:alignment.assay_type != ‘auto’
alignment.n_reads
label:Number of reads in subsampled alignment file
type:basic:integer
description:Alignment (.bam) file subsample size. Increase the number of reads to make automatic detection more reliable. Decrease the number of reads to make automatic detection run faster.
hidden:alignment.assay_type != ‘auto’
default:5000000
annotation.annotation
label:Annotation
type:data:annotation
description:GTF and GFF3 annotation formats are supported.
annotation.feature_class
label:Feature class
type:basic:string
description:Feature class (3rd column in GTF/GFF3 file) to be used. All other features will be ignored.
default:exon
annotation.feature_type
label:Feature type
type:basic:string
description:The type of feature the quantification program summarizes over (e.g. gene or transcript-level analysis). The value of this parameter needs to be chosen in line with ‘ID attribute’ below.
default:gene
choices:
  • gene: gene
  • transcript: transcript
annotation.id_attribute
label:ID attribute
type:basic:string
description:GTF/GFF3 attribute to be used as feature ID. Several GTF/GFF3 lines with the same feature ID will be considered as parts of the same feature. The feature ID is used to identify the counts in the output table. In GTF files this is usually ‘gene_id’, in GFF3 files this is often ‘ID’, and ‘transcript_id’ is frequently a valid choice for both annotation formats.
default:gene_id
choices:
  • gene_id: gene_id
  • transcript_id: transcript_id
  • ID: ID
  • geneid: geneid
normalization_type
label:Normalization type
type:basic:string
description:The default expression normalization type.
default:TPM
choices:
  • TPM: TPM
  • CPM: CPM
  • FPKM: FPKM
  • RPKUM: RPKUM
mappability
label:Mappability
type:data:mappability:bcm
description:Genome mappability information
required:False
hidden:normalization_type != ‘RPKUM’
show_advanced
label:Show advanced options
type:basic:boolean
description:Inspect and modify parameters
default:False
advanced.summarization_level.count_features
label:Perform read counting at feature level
type:basic:boolean
description:Count reads for exons rather than genes.
default:False
advanced.overlap.allow_multi_overlap
label:Assign reads to all their overlapping features or meta-features
type:basic:boolean
default:False
advanced.overlap.min_overlap
label:Minimum number of overlapping bases in a read that is required for read assignment
type:basic:integer
description:Number of overlapping bases is counted from both reads if paired-end. If a negative value is provided, then a gap of up to specified size will be allowed between read and the feature that the read is assigned to.
default:1
advanced.overlap.frac_overlap
label:Minimum fraction of overlapping bases in a read that is required for read assignment
type:basic:decimal
description:Value should be within range [0, 1]. Number of overlapping bases is counted from both reads if paired end. Both this option and ‘Minimum number of overlapping bases in a read that is required for read assignment’ need to be satisfied for read assignment.
default:0.0
advanced.overlap.frac_overlap_feature
label:Minimum fraction of overlapping bases included in a feature that is required for overlapping with a read or a read pair
type:basic:decimal
description:Value should be within range [0, 1].
default:0.0
advanced.overlap.largest_overlap
label:Assign reads to a feature or meta-feature that has the largest number of overlapping bases
type:basic:boolean
default:False
advanced.overlap.read_extension_5
label:Number of bases to extend reads upstream by from their 5’ end
type:basic:integer
default:0
advanced.overlap.read_extension_3
label:Number of bases to extend reads upstream by from their 3’ end
type:basic:integer
default:0
advanced.overlap.read_to_pos
label:Reduce reads to their 5’-most or 3’-most base
type:basic:integer
description:Read counting is performed based on the single base the read is reduced to.
required:False
advanced.multi_mapping_reads.count_multi_mapping_reads
label:Count multi-mapping reads
type:basic:boolean
description:For a multi-mapping read, all its reported alignments will be counted. The ‘NH’ tag in BAM input is used to detect multi-mapping reads.
default:False
advanced.fractional_counting.fraction
label:Assign fractional counts to features
type:basic:boolean
description:This option must be used together with ‘Count multi-mapping reads’ or ‘Assign reads to all their overlapping features or meta-features’ or both. When ‘Count multi-mapping reads’ is checked, each reported alignment from a multi-mapping read (identified via ‘NH’ tag) will carry a count of 1 / x, instead of 1 (one), where x is the total number of alignments reported for the same read. When ‘Assign reads to all their overlapping features or meta-features’ is checked, each overlapping feature will receive a count of 1 / y, where y is the total number of features overlapping with the read. When both ‘Count multi-mapping reads’ and ‘Assign reads to all their overlapping features or meta-features’ are specified, each alignment will carry a count of 1 / (x * y).
required:False
disabled:!advanced.multi_mapping_reads.count_multi_mapping_reads && !advanced.overlap.allow_multi_overlap
default:False
advanced.read_filtering.min_mqs
label:Minimum mapping quality score
type:basic:integer
description:The minimum mapping quality score a read must satisfy in order to be counted. For paired-end reads, at least one end should satisfy this criterion.
default:0
advanced.read_filtering.split_only
label:Count only split alignments
type:basic:boolean
default:False
advanced.read_filtering.non_split_only
label:Count only non-split alignments
type:basic:boolean
default:False
advanced.read_filtering.primary
label:Count only primary alignments
type:basic:boolean
description:Primary alignments are identified using bit 0x100 in BAM FLAG field.
default:False
advanced.read_filtering.ignore_dup
label:Ignore duplicate reads in read counting
type:basic:boolean
description:Duplicate reads are identified using bit Ox400 in BAM FLAG field. The whole read pair is ignored if one of the reads is a duplicate read for paired-end data.
default:False
advanced.exon_exon_junctions.junc_counts
label:Count number of reads supporting each exon-exon junction
type:basic:boolean
description:Junctions are identified from those exon-spanning reads in input (containing ‘N’ in CIGAR string).
default:False
advanced.exon_exon_junctions.genome
label:Genome
type:data:genome
description:Reference sequences used in read mapping that produced the provided BAM files. This optional argument can be used to improve read counting for junctions.
required:False
disabled:!advanced.exon_exon_junctions.junc_counts
advanced.paired_end.is_paired_end
label:Count fragments (or templates) instead of reads
type:basic:boolean
default:True
advanced.paired_end.require_both_ends_mapped
label:Count only read pairs that have both ends aligned
type:basic:boolean
default:False
advanced.paired_end.check_frag_length
label:Check fragment length when assigning fragments to meta-features or features
type:basic:boolean
description:Use minimum and maximum fragment/template length to set thresholds.
default:False
advanced.paired_end.min_frag_length
label:Minimum fragment/template length
type:basic:integer
required:False
disabled:!advanced.paired_end.check_frag_length
default:50
advanced.paired_end.max_frag_length
label:Maximum fragment/template length
type:basic:integer
required:False
disabled:!advanced.paired_end.check_frag_length
default:600
advanced.paired_end.do_not_count_chimeric_fragments
label:Do not count chimeric fragments
type:basic:boolean
description:Do not count read pairs that have their two ends mapped to different chromosomes or mapped to same chromosome but on different strands.
default:False
advanced.paired_end.do_not_sort
label:Do not sort reads in BAM input
type:basic:boolean
default:False
advanced.read_groups.by_read_group
label:Assign reads by read group
type:basic:boolean
description:RG tag is required to be present in the input BAM files.
default:False
advanced.long_reads.count_long_reads
label:Count long reads such as Nanopore and PacBio reads
type:basic:boolean
default:False
advanced.miscellaneous.report_reads
label:Output detailed assignment results for each read or read pair
type:basic:boolean
default:False
advanced.miscellaneous.max_mop
label:Maximum number of ‘M’ operations allowed in a CIGAR string
type:basic:integer
description:Both ‘X’ and ‘=’ are treated as ‘M’ and adjacent ‘M’ operations are merged in the CIGAR string.
default:10
advanced.miscellaneous.verbose
label:Output verbose information
type:basic:boolean
description:Output verbose information for debugging, such as unmatched chromosome / contig names.
default:False

Output results

rc
label:Read counts
type:basic:file
fpkm
label:FPKM
type:basic:file
tpm
label:TPM
type:basic:file
cpm
label:CPM
type:basic:file
exp
label:Default expression output
type:basic:file
exp_json
label:Default expression output (json)
type:basic:json
exp_type
label:Expression normalization type (on default output)
type:basic:string
exp_set
label:Expressions
type:basic:file
exp_set_json
label:Expressions (json)
type:basic:json
feature_counts_output
label:featureCounts output
type:basic:file
counts_summary
label:Counts summary
type:basic:file
read_assignments
label:Read assignments
type:basic:file
description:Read assignment results for each read (or fragment if paired end).
required:False
strandedness_report
label:Strandedness report file
type:basic:file
required:False
source
label:Gene ID database
type:basic:string
species
label:Species
type:basic:string
build
label:Build
type:basic:string
feature_type
label:Feature type
type:basic:string
methcounts
data:wgbs:methcountsmethcounts (data:genome:fasta  genome, data:alignment:mr  alignment, basic:boolean  cpgs, basic:boolean  symmetric_cpgs)[Source: v1.0.1]

The methcounts program takes the mapped reads and produces the methylation level at each genomic cytosine, with the option to produce only levels for CpG-context cytosines.

Input arguments

genome
label:Reference genome
type:data:genome:fasta
alignment
label:Mapped reads
type:data:alignment:mr
description:WGBS alignment file in Mapped Read (.mr) format.
cpgs
label:Only CpG context sites
type:basic:boolean
description:Output file will contain methylation data for CpG context sites only. Choosing this option will result in CpG content report only.
disabled:symmetric_cpgs
default:False
symmetric_cpgs
label:Merge CpG pairs
type:basic:boolean
description:Merging CpG pairs results in symmetric methylation levels. Methylation is usually symmetric (cytosines at CpG sites were methylated on both DNA strands). Choosing this option will only keep the CpG sites data.
disabled:cpgs
default:True

Output results

meth
label:Methylation levels
type:basic:file
stats
label:Statistics
type:basic:file
bigwig
label:Methylation levels BigWig file
type:basic:file
species
label:Species
type:basic:string
build
label:Build
type:basic:string
miRNA pipeline
data:workflow:mirnaworkflow-mirna (data:reads:fastq  reads, data:genome:fasta  genome, data:annotation  annotation, basic:string  id_attribute, basic:string  feature_class)[Source: v0.0.5]

Input arguments

reads
label:Input miRNA reads.
type:data:reads:fastq
description:Note that these reads should already be void of adapters.
genome
label:Genome
type:data:genome:fasta
annotation
label:Annotation (GTF/GFF3)
type:data:annotation
id_attribute
label:ID attribute
type:basic:string
description:GTF/GFF3 attribute to be used as feature ID. Several GTF/GFF3 lines with the same feature ID will be considered as parts of the same feature. The feature ID is used to identify the counts in the output table. In GTF files this is usually ‘gene_id’, in GFF3 files this is often ‘ID’, and ‘transcript_id’ is frequently a valid choice for both annotation formats.
default:gene_id
choices:
  • gene_id: gene_id
  • transcript_id: transcript_id
  • ID: ID
  • geneid: geneid
feature_class
label:Feature class
type:basic:string
description:Feature class (3rd column in GFF file) to be used, all features of other types are ignored.
default:miRNA

Output results

snpEff
data:snpeff:uploadupload-snpeff (basic:file  annotation, basic:file  summary, basic:file  snpeff_genes)[Source: v1.1.1]

Upload snpEff result files.

Input arguments

annotation
label:Annotation file
type:basic:file
summary
label:Summary
type:basic:file
snpeff_genes
label:SnpEff genes
type:basic:file

Output results

annotation
label:Annotation file
type:basic:file
summary
label:Summary
type:basic:file:html
snpeff_genes
label:SnpEff genes
type:basic:file
snpEff
data:snpeffsnpeff (data:variants:vcf  variants, basic:string  var_source, basic:string  database, list:data:variants:vcf  known_vars_annot)[Source: v0.2.1]

Variant annotation using snpEff package.

Input arguments

variants
label:Variants (VCF)
type:data:variants:vcf
var_source
label:Input VCF source
type:basic:string
choices:
  • GATK HC: gatk_hc
  • loFreq: lofreq
database
label:snpEff database
type:basic:string
default:GRCh37.75
choices:
  • GRCh37.75: GRCh37.75
known_vars_annot
label:Known variants
type:list:data:variants:vcf

Output results

annotation
label:Annotation file
type:basic:file
summary
label:Summary
type:basic:file:html
snpeff_genes
label:SnpEff genes
type:basic:file

Descriptor schemas

When working with the biological data, it is recommended (and often required) to properly annotate samples. The annotation information attached to the samples includes information about organism, source, cell type, library preparation protocols and others.

The annotation fields associated with the samples or related sample files are defined in the descriptor schemas. This tutorial describes the descriptor schemas that are attached to the sample objects, raw sequencing reads and differential expressions files.

Other available descriptor schemas can be explored at the Resolwe-bio GitHub page. Customized descriptor schemas can be created using the Resolwe SDK.

Sample

When a new data object that represents a biological sample (i.e. fastq files, bam files) is uploaded to the database, the unannotated sample ( presample) is automatically created. When annotation is attached to the presample object, this object is automatically converted to the annotated sample. To annotate the sample, we need to define a descriptor schema that will be used for the annotation. Together with the descriptor schema, we need to provide the annotations (descriptors) that populate the annotation fields defined in the descriptor shema. The details of this process are described in the Resolwe SDK documentation.

To annotate the sample in a GEO compliant way, we prepared the sample annotation schema. An example of the customized descriptor schema is also available.

Reads

To annotate raw sequencing reads we have prepared two descriptor schemas: reads and reads_detailed.

Differential expression

To define the default thresholds for p-value, log fold change (FC) and to describe which samples are used as cases and which as controls in the calculation of differential expression we have prepared diffexp descriptor schema.

Reference

Utilities

Test helper functions.

class resolwe_bio.utils.test.BioProcessTestCase(methodName='runTest')[source]

Base class for writing bioinformatics process tests.

It is a subclass of Resolwe’s ProcessTestCase with some specific functions used for testing bioinformatics processes.

prepare_adapters(fn='adapters.fasta')[source]

Prepare adapters FASTA.

prepare_amplicon_master_file(mfile='56G_masterfile_test.txt', pname='56G panel, v2')[source]

Prepare amplicon master file.

prepare_annotation(fn='sp_test.gtf', source='DICTYBASE', species='Dictyostelium discoideum', build='dd-05-2009')[source]

Prepare annotation GTF.

prepare_annotation_gff(fn='annotation dicty.gff.gz', source='DICTYBASE', species='Dictyostelium discoideum', build='dd-05-2009')[source]

Prepare annotation GFF3.

prepare_bam(fn='sp_test.bam', species='Dictyostelium discoideum', build='dd-05-2009')[source]

Prepare alignment BAM.

prepare_expression(f_rc='exp_1_rc.tab.gz', f_exp='exp_1_tpm.tab.gz', f_type='TPM', name='Expression', source='DICTYBASE', descriptor=None, feature_type='gene', species='Dictyostelium discoideum', build='dd-05-2009')[source]

Prepare expression.

prepare_genome()[source]

Prepare genome FASTA.

prepare_paired_reads(mate1=['fw reads.fastq.gz'], mate2=['rw reads.fastq.gz'])[source]

Prepare NGS reads FASTQ.

prepare_reads(fn=['reads.fastq.gz'])[source]

Prepare NGS reads FASTQ.

setUp()[source]

Initialize test files path.

class resolwe_bio.utils.test.KBBioProcessTestCase(methodName='runTest')[source]

Class for bioinformatics process tests that use knowledge base.

It is based on BioProcessTestCase and Django’s LiveServerTestCase. The latter launches a live Django server in a separate thread so that the tests may use it to query the knowledge base.

setUp()[source]

Set-up test gene information knowledge base.

resolwe_bio.utils.test.skipDockerFailure(reason)[source]

Skip decorated tests due to failures when run in Docker.

Unless TESTS_SKIP_DOCKER_FAILURES Django setting is set to False. reason should describe why the test is being skipped.

resolwe_bio.utils.test.skipUnlessLargeFiles(*files)[source]

Skip decorated tests unless large files are available.

Parameters:*files (list) – variable lenght files list, where each element represents a large file path relative to the TEST_LARGE_FILES_DIR directory

Change Log

All notable changes to this project are documented in this file. This project adheres to Semantic Versioning.

Unreleased

Added
  • Add alleyoop-rates process
  • Add alleyoop-utr-rates process
  • Add alleyoop-summary process
  • Add alleyoop-snpeval process
  • Add alleyoop-collapse process
  • Add slam-count process
  • Add workflow-slamdunk-paired workflow
Changed
  • BACKWARD INCOMPATIBLE: Refactor slamdunk-all-paired process to support genome browser visualization and add additional output fields
  • Append sample and genome reference information to the summary output file in the filtering-chemut process
  • Bigwig output field in bamclipper, bqsr and markduplicates processes is no longer required
  • Freeze docutils package version to 0.15.2 because Sphinx has problems parsing development version numbers
  • Support Slamdunk/Alleyoop processes in MultiQC
  • Enable sorting of files in alignment-star process using samtools

24.0.0 - 2019-11-15

Added
  • Add resolwebio/slamdunk Docker image
  • Add Tabix (1.7-2) to resolwebio/bamliquidator:1.2.0 Docker image
  • Add seqtk-rev-complement-single and seqtk-rev-complement-paired process
  • Add slamdunk-all-paired process
Changed
  • BACKWARD INCOMPATIBLE: Require Resolwe 20.x
  • Make BaseSpace file download more robust
  • Bump rose2 to 1.1.0, bamliquidator to 1.3.8, and use resolwebio/base:ubuntu-18.04 Docker image as a base image in resolwebio/bamliquidator:1.1.0 Docker image
  • Use resolwebio/bamliquidator:1.2.0 in rose2 process
  • Bump CPU, memory and Docker image (resolwebio/rnaseq:4.9.0) requirements in alignment-bwa-mem, alignment-bwa-sw and alignment-bwa-aln processes
  • Use multi-threading option in Samtools commands in alignment-bwa-mem, alignment-bwa-sw and alignment-bwa-aln processes
  • Support merging of multi-lane sequencing data into a single (pair) of FASTQ files in the upload-fastq-single, upload-fastq-paired, files-to-fastq-single and files-to-fastq-paired processes.

23.1.1 - 2019-10-11

Changed
  • Renamed workflow-trim-align-quant workflow to make the name more informative

23.1.0 - 2019-09-30

Added
  • Add Macaca mulatta species choice to the sample descriptor schema
  • Add workflow-cutadapt-star-fc-quant-wo-depletion-single process
Changed
  • Test files improved for workflow-wes, bamclipper, markduplicates and bqsr
  • Fix typo in differentialexpression-shrna process docstring
Fixed
  • Fix transcript-to-gene_id mapping for Salmon expressions in differentialexpression-deseq2 process. Transcript versions are now ignored when matching IDs using the transcript-to-gene_id mapping table.
  • Fix workflow-cutadapt-star-fc-quant-single process description

23.0.0 - 2019-09-17

Changed
  • Update order of QC reports in MultiQC configuration file. The updated configuration file is part of the resolwebio/common:1.3.1 Docker image.
  • Bump Jbrowse to version 1.16.6 in resolwebio/rnaseq:4.9.0 Docker image
  • Use JBrowse generate-names.pl script to index GTF/GFF3 features upon annotation file upload
  • Support Salmon reports in MultiQC and expose dirs_depth parameter
  • Expose transcript-level expression file in the salmon-quant process
Added
  • Add workflow-bbduk-salmon-qc-single and workflow-bbduk-salmon-qc-paired workflows
Fixed
  • Give process upload-bedpe access to network

22.0.0 - 2019-08-20

Changed
  • BACKWARD INCOMPATIBLE: Require Resolwe 19.x
  • BACKWARD INCOMPATIBLE: Unify cutadapt-single and cutadapt-paired process inputs and refactor to use Cutadapt v2.4
  • Expose BetaPrior parameter in differentialexpression-deseq2 process
  • Install R from CRAN-maintained repositories in Docker images build from the resolwebio/base:ubuntu-18.04 base image
  • Prepare resolwebio/common:1.3.0 Docker image:
    • Install R v3.6.1
    • Bump Resdk to v10.1.0
    • Install gawk package
    • Fix Docker image build issues
  • Use resolwebio/common:1.3.0 as a base image for resolwebio/rnaseq:4.8.0
  • Update StringTie to v2.0.0 in resolwebio/rnaseq:4.8.0
  • Support StringTie analysis results in DESeq2 tool
Added
  • Add cutadapt-3prime-single process
  • Add workflow-cutadapt-star-fc-quant-single process
  • Add argument skip to bamclipper which enables skipping of the said process
  • Add cutadapt-corall-single and cutadapt-corall-paired processes for pre-processing of reads obtained using Corall Total RNA-seq library prep kit
  • Add umi-tools-dedup process
  • Add stringtie process
  • Add workflow-corall-single and workflow-corall-paired workflows optimized for Corall Total RNA-seq library prep kit data
Fixed
  • Fix warning message in hierarchical clustering of genes. Incorrect gene names were reported in the warning message about removed genes. Computation of hierarchical clustering was correct.

21.0.1 - 2019-07-26

Changed
  • Bump Cutadapt to v2.4 and use resolwebio/common:1.2.0 as a base image in resolwebio/rnaseq:4.6.0
Added
  • Add pigz package to resolwebio/common:1.2.0 Docker image
  • Add StringTie and UMI-tools to resolwebio/rnaseq:4.7.0 Docker image
Fixed
  • Fix spikeins-qc process to correctly handle the case where all expressions are without spikeins
  • Fix an error in macs2-callpeak process that prevented correct reporting of build/species mismatch between inputs
  • Support UCSC annotations in feature_counts process by assigning empty string gene_ids to the “unknown” gene

21.0.0 - 2019-07-16

Changed
  • BACKWARD INCOMPATIBLE: Require Resolwe 18.x
  • Bump the number of allocated CPU cores to 20 in alignment-bwa-mem process
  • Bump memory requirements in seqtk-sample-single and seqtk-sample-paired processes
  • Bump Salmon to v0.14.0 in resolwebio/rnaseq:4.5.0 Docker image
  • Expose additional inputs in salmon-index process
  • Use resolwebio/rnaseq:4.5.0 Docker image in processes that call Salmon tool (library-strandedness, feature_counts and qorts-qc)
  • Implement dropdown menu for upload-bedpe process
  • Add validation stringency parameter to bqsr process and propagate it to the workflow-wes as well
  • Add LENIENT value to validation stringency parameter of the markduplicates process
  • Improve performance of RPKUM normalization in featureCounts process
Added
  • Add salmon-quant process
Fixed
  • Fix genome upload process to correctly handle filenames with dots
  • Fix merging of expressions in archive-samples process. Previously some genes were missing in the merged expression files. The genes that were present had expression values correctly assigned. The process was optimized for performance and now supports parallelization.

20.0.0 2019-06-19

Changed
  • BACKWARD INCOMPATIBLE: Require Resolwe 17.x
  • BACKWARD INCOMPATIBLE: Use Elasticsearch version 6.x
  • BACKWARD INCOMPATIBLE: Bump Django requirement to version 2.2
  • BACKWARD INCOMPATIBLE: Remove obsolete RNA-seq workflows workflow-bbduk-star-featurecounts-single, workflow-bbduk-star-featurecounts-paired, workflow-cutadapt-star-featurecounts-single and workflow-cutadapt-star-featurecounts-paired
  • BACKWARD INCOMPATIBLE: Remove obsolete descriptor schemas: rna-seq-bbduk-star-featurecounts, quantseq, rna-seq-cutadapt-star-featurecounts and kapa-rna-seq-bbduk-star-featurecounts
  • BACKWARD INCOMPATIBLE: In upload-fasta-nucl process, store compressed and uncompressed FASTA files in fastagz and fasta ouput fields, respectively
  • Allow setting the Java memory usage flags for the QoRTs tool in resolwebio/common:1.1.3 Docker image
  • Use resolwebio/common:1.1.3 Docker image as a base image for resolwebio/rnaseq:4.4.2
  • Bump GATK4 version to 4.1.2.0 in resolwebio/dnaseq:4.2.0
  • Use MultiQC configuration file and prepend directory name to sample names by default in multiqc process
  • Bump resolwebio/common to 1.1.3 in resolwebio/dnaseq:4.2.0
  • Process vc-gatk4-hc now also accepts BED files through parameter intervals_bed
Added
  • Support Python 3.7
  • Add Tabix (1.7-2) to resolwebio/wgbs docker image
  • Add JBrowse index output to hmr process
  • Add bamclipper tool and parallel package to resolwebio/dnaseq:4.2.0 image
  • Support hg19_mm10 hybrid genome in bam-split process
  • Support mappability-based normalization (RPKUM) in featureCounts
  • Add BEDPE upload process
  • Add bamclipper process
  • Add markduplicates process
  • Add bqsr (BaseQualityScoreRecalibrator) process
  • Add whole exome sequencing (WES) pipeline
Fixed
  • Fix building problems of resolwebio/dnaseq docker
  • Fix handling of no-adapters input in workflows workflow-bbduk-star-featurecounts-qc-single and workflow-bbduk-star-featurecounts-qc-paired

19.0.1 2019-05-13

Fixed
  • Use resolwebio/rnaseq:4.4.2 Docker image that enforces the memory limit and bump memory requirements for qorts-qc process
  • Bump memory requirements for multiqc process

19.0.0 2019-05-07

Changed
  • Use Genialis fork of MultiQC 1.8.0b in resolwebio/common:1.1.2
  • Support Samtools idxstats and QoRTs QC reports in multiqc process
  • Support samtools-idxstats QC step in workflows:
    • workflow-bbduk-star-featurecounts-qc-single
    • workflow-bbduk-star-featurecounts-qc-paired
    • workflow-bbduk-star-fc-quant-single
    • workflow-bbduk-star-fc-quant-paired
  • Simplify cellranger-count outputs folder structure
  • Bump STAR aligner to version 2.7.0f in resolwebio/rnaseq:4.4.1 Docker image
  • Use resolwebio/rnaseq:4.4.1 in alignment-star and alignment-star-index processes
  • Save filtered count-matrix output file produced by DESeq2 differential expression process
Added
  • Add samtools-idxstats process
  • Improve cellranger-count and cellranger-mkref logging
  • Add FastQC report to upload-sc-10x process
Fixed
  • Fix archive-samples to work with data:chipseq:callpeak:macs2 data objects when downloading only peaks without QC reports
  • Fix parsing gene set files with empty lines to avoid saving gene sets with empty string elements

18.0.0 2019-04-16

Changed
  • BACKWARD INCOMPATIBLE: Require Resolwe 16.x
  • BACKWARD INCOMPATIBLE: Rename and improve descriptions of processes specific to CATS RNA-seq kits. Remove related cutadapt-star-htseq descriptor schema.
  • BACKWARD INCOMPATIBLE: Remove workflow-accel-gatk4 pipeline. Remove amplicon-panel, amplicon-panel-advanced and amplicon-master-file descriptor schemas.
  • BACKWARD INCOMPATIBLE: Remove obsolete processes and descriptor schemas: rna-seq-quantseq, bcm-workflow-rnaseq, bcm-workflow-chipseq, bcm-workflow-wgbs, dicty-align-reads, dicty-etc, affy and workflow-chip-seq
  • Expose additional parameters of bowtie2 process
  • Support strandedness auto detection in qorts-qc process
Added
  • Add shRNAde (v1.0) R package to the resolwebio/rnaseq:4.4.0 Docker image
  • Add resolwebio/scseq Docker image
  • Add shRNA differential expression process. This is a two-step process which trims, aligns and quantifies short hairpin RNA species. These are then used in a differential expression.
  • Add sc-seq processes:
    • cellranger-mkref
    • cellranger-count
    • upload-sc-10x
    • upload-bam-scseq-indexed
Fixed
  • Bump memory requirements in seqtk-sample-single and seqtk-sample-paired processes
  • Fix cellranger-count html report
  • Mark spliced-alignments with XS flags in workflow-rnaseq-cuffquant
  • Fix whitespace handling in cuffnorm process

17.0.0 2019-03-19

Added
  • Add qorts-qc (Quality of RNA-seq Tool-Set QC) process
  • Add workflow-bbduk-star-fc-quant-single and workflow-bbduk-star-fc-quant-paired processes
  • Add independent gene filtering and gene filtering based on Cook’s distance in DESeq2 differential expression process
Changed
  • BACKWARD INCOMPATIBLE: Move gene filtering by expression count input to filter.min_count_sum in DESeq2 differential expression process
  • BACKWARD INCOMPATIBLE: Require Resolwe 15.x
  • Update resolwebio/common:1.1.0 Docker image:
    • add QoRTs (1.3.0) package
    • bump MultiQC to 1.7.0
    • bump Subread package to 1.6.3
  • Expose maxns input parameter in bbduk-single and bbduk-paired processes. Make this parameter available in workflows workflow-bbduk-star-featurecounts-qc-single, workflow-bbduk-star-featurecounts-qc-paired, workflow-bbduk-star-featurecounts-single and workflow-bbduk-star-featurecounts-paired.
  • Save CPM-normalized expressions in feature_counts process. Control the default expression normalization type (exp_type) using the normalization_type input.
  • Bump MultiQC to version 1.7.0 in multiqc process
  • Use resolwebio/rnaseq:4.3.0 with Subread/featureCounts version 1.6.3 in feature_counts process

16.3.0 2019-02-19

Changed
  • Bump STAR aligner version to 2.7.0c in resolwebio/rnaseq:4.2.2
  • Processes alignment-star and alignment-star-index now use Docker image resolwebio/rnaseq:4.2.2 which contains STAR version 2.7.0c
  • Persistence of basespace-file-import process changed from RAW to TEMP
Added
  • Make prepare-geo-chipseq work with both data:chipseq:callpeak:macs2 and data:chipseq:callpeak:macs14 as inputs
Fixed
  • Report correct total mapped reads and mapped reads percentage in prepeak QC report for data:alignment:bam:bowtie2 inputs in macs2-callpeak process

16.2.0 2019-01-28

Changed
  • Enable multithreading mode in alignment-bwa-aln and alignment-bwa-sw
  • Lineary lower the timeout for BigWig calculation when running on multiple cores
Fixed
  • Remove pip --process-dependency-links argument in testenv settings
  • Fix walt getting killed when sort runs out of memory. The sort command buffer size was limited to the process memory limit.

16.1.0 2019-01-17

Changed
Added
  • Add the FASTQ file validator script to the upload-fastq-single, upload-fastq-paired, files-to-fastq-single and files-to-fastq-paired processes
  • Add spikein-qc process
  • Add to resolwebio/rnaseq:4.1.0 Docker image:
    • dnaio Python library
  • Add to resolwebio/rnaseq:4.2.0 Docker image:
    • ERCC table
    • common Genialis fonts and css file
    • spike-in QC report template
  • Set MPLBACKEND environment variable to Agg in resolwebio/common:1.0.1 Docker image
Fixed
  • Fix the format of the output FASTQ file in the demultiplex.py script
  • Fix NSC and RSC QC metric calculation for ATAC-seq and paired-end ChIP-seq samples in macs2-callpeak and qc-prepeak processes

16.0.0 2018-12-19

Changed
  • BACKWARD INCOMPATIBLE: Require Resolwe 14.x
  • BACKWARD INCOMPATIBLE: Remove obsolete processes findsimilar
  • BACKWARD INCOMPATIBLE: Include ENCODE-proposed QC analysis metrics methodology in the macs2-callpeak process. Simplified MACS2 analysis inputs now allow the use of sample relations (treatment/background) concept to trigger multiple MACS2 jobs automatically using the macs2-batch or macs2-rose2-batch processes.
  • BACKWARD INCOMPATIBLE: Update workflow-atac-seq inputs to match the updated macs2-callpeak process
  • Use resolwebio/rnaseq:4.0.0 Docker image in alignment-star-index, bbduk-single, bbduk-paired, cuffdiff, cufflinks, cuffmerge, cuffnorm, cuffquant, cutadapt-custom-single, cutadapt-custom-paired, cutadapt-single, cutadapt-paired, differentialexpression-deseq2, differentialexpression-edger, expression-aggregator, feature_counts, goenrichment, htseq-count, htseq-count-raw, index-fasta-nucl, library-strandedness, pca, regtools-junctions-annotate, rsem, salmon-index, trimmomatic-single, trimmomatic-paired, upload-expression, upload-expression-cuffnorm, upload-expression-star, upload-fasta-nucl, upload-fastq-single, upload-fastq-paired, files-to-fastq-single, files-to-fastq-paired, upload-gaf, upload-genome, upload-gff3, upload-gtf and upload-obo
  • Order statistical groups in expression aggregator output by sample descriptor field value
  • Use resolwebio/biox:1.0.0 Docker image in etc-bcm, expression-dicty and mappability-bcm processes
  • Use resolwebio/common:1.0.0 Docker image in amplicon-table, mergeexpressions, upload-diffexp, upload-etc, upload-multiplexed-single and upload-multiplexed-paired processes
  • Use resolwebio/base:ubuntu-18.04 Docker image in create-geneset, create-geneset-venn, mergeetc, prepare-geo-chipseq, prepare-geo-rnaseq, upload-cxb, upload-geneset, upload-header-sam, upload-mappability, upload-snpeff and upload-picard-pcrmetrics processes
  • Update GATK4 to version 4.0.11.0 in resolwebio/dnaseq:4.1.0 Docker image. Install and use JDK v8 by default to ensure compatibility with GATK4 package.
  • Use resolwebio/dnaseq:4.1.0 Docker image in align-bwa-trim, coveragebed, filtering-chemut, lofreq, picard-pcrmetrics, upload-master-file, upload-variants-vcf and vc-gatk4-hc processes
  • Expose reads quality filtering (q) parameter, reorganize inputs and rename the stats output file in alignment-bwa-aln process
  • Use resolwebio/chipseq:4.0.0 Docker image in chipseq-genescore, chipseq-peakscore, macs14, upload-bed and qc-prepeak processes
  • Use resolwebio/bamliquidator:1.0.0 Docker image in bamliquidator and bamplot processes
Added
  • Add biosample source field to sample descriptor schema
  • Add background_pairs Jinja expressions filter that accepts a list of data objects and orders them in a list of pairs (case, background) based on the background relation between corresponding samples
  • Add chipseq-bwa descriptor schema. This schema specifies the default inputs for BWA ALN aligner process as defined in ENCODE ChIP-Seq experiments.
  • Add support for MACS2 result files to MultiQC process
  • Add macs2-batch, macs2-rose2-batch and workflow-macs-rose processes
  • Add feature symbols to expressions in archive-samples process
Fixed
  • Make ChIP-seq fields in sample descriptor schema visible when ChIPmentation assay type is selected
  • Fix handling of whitespace in input BAM file name in script detect_strandedness.sh
  • Set available memory for STAR aligner to 36GB. Limit the available memory for STAR aligner --limitBAMsortRAM parameter to 90% of the Docker requirements setting
  • Set bbduk-single and bbduk-paired memory requirements to 8GB
  • Fix wrong file path in archive-samples process

15.0.0 2018-11-20

Changed
  • BACKWARD INCOMPATIBLE: Remove obsolete processes: bsmap, mcall, coverage-garvan, igv, jbrowse-bed, jbrowse-gff3, jbrowse-gtf, jbrowse-bam-coverage, jbrowse-bam-coverage-normalized, jbrowse-refseq, fastq-mcf-single, fastq-mcf-paired, hsqutils-trim, prinseq-lite-single, prinseq-lite-paired, sortmerna-single, sortmerna-paired, bam-coverage, hsqutils-dedup, vc-samtools, workflow-heat-seq and alignment-tophat2
  • BACKWARD INCOMPATIBLE: Remove jbrowse-bam-coverage process step from the workflow-accel workflow. The bigwig coverage track is computed in align-bwa-trim process instead.
  • BACKWARD INCOMPATIBLE: Remove resolwebio/utils Docker image. This image is replaced by the resolwebio/common image.
  • BACKWARD INCOMPATIBLE: Use resolwebio/common Docker image as a base image for the resolwebio/biox, resolwebio/chipseq, resolwebio/dnaseq and resolwebio/rnaseq images
  • BACKWARD INCOMPATIBLE: Remove resolwebio/legacy Docker image.
  • Use sample name as the name of the data object in:
    • alignment-bwa-aln
    • alignment-bowtie2
    • qc-prepeak
    • macs2-callpeak
  • Attach macs2-callpeak, macs14 and rose2 process data to the case/treatment sample
  • Use resolwebio/dnaseq:4.0.0 docker image in align-bwa-trim process
  • Use resolwebio/rnaseq:4.0.0 docker image in aligners: alignment-bowtie, alignment-bowtie2, alignment-bwa-mem, alignment-bwa-sw, alignment-bwa-aln, alignment-hisat2, alignment-star and alignment-subread.
  • Set memory limits in upload-genome, trimmomatic-single and trimmomatic-paired processes
  • Improve error messages in differential expression process DESeq2
Added
  • Add makedb (WALT 1.01) - callable as makedb-walt, tool to create genome index for WALT aligner, to resolwebio/rnaseq docker image
  • Add resolwebio/wgbs docker image including the following tools:
    • MethPipe (3.4.3)
    • WALT (1.01)
    • wigToBigWig (kent-v365)
  • Add resolwebio/common Docker image. This image includes common bioinformatics utilities and can serve as a base image for other, specialized resolwebio Docker images: resolwebio/biox, resolwebio/chipseq, resolwebio/dnaseq and resolwebio/rnaseq.
  • Add shift (user-defined cross-correlation peak strandshift) input to qc-prepeak process
  • Add ATAC-seq workflow
  • Compute index for WALT aligner on genome upload and support uploading the index together with the genome
  • Add Whole genome bisulfite sequencing workflow and related WGBS processes:
    • WALT
    • methcounts
    • HMR
  • Add bedClip to resolwebio/chipseq:3.1.0 docker image
  • Add resolwebio/biox Docker image. This image is based on the resolwebio/common image and includes Biox Python library for Dictyostelium RNA-Seq analysis support.
  • Add resolwebio/snpeff Docker image. The image includes SnpEff (4.3K) tool.
  • Add spike-in names, rRNA and globin RNA cromosome names in resolwebio/common image
  • Add UCSC bedGraphtoBigWig tool for calculating BigWig in bamtobigwig.sh script. In align-bwa-trim processor set this option (that BigWig is calculated by UCSC tool instead of deepTools), because it is much faster for amplicon files. In other processors update the input parameters for bamtobigwig.sh: alignment-bowtie, alignment-bowtie2, alignment-bwa-mem, alignment-bwa-sw, alignment-bwa-aln, alignment-hisat2, alignment-star alignment-subread, upload-bam, upload-bam-indexed and upload-bam-secondary.
  • In bamtobigwig.sh don’t create BigWig when bam file was aligned on globin RNA or rRNA (this are QC steps and BigWig is not needed)
Fixed
  • BACKWARD INCOMPATIBLE: Use user-specificed distance metric in hierarchical clustering
  • Handle integer expression values in hierarchical clustering
  • Fix Amplicon table gene hyperlinks for cases where multiple genes are associated with detected variant
  • Handle empty gene name in expression files in PCA
  • Fix PBC QC reporting in qc-prepeak process for a case where there are no duplicates in the input bam
  • Fix macs2-callpeak process so that user defined fragment lenth has priority over the qc-prepeak estimated fragment length when shifting reads for post-peakcall QC
  • Fix macs2-callpeak to prevent the extension of intervals beyond chromosome boundaries in MACS2 bedgraph outputs
  • Fix warning message in hierarchical clustering of genes to display gene names

14.0.2 2018-10-23

Fixed
  • Fix htseq-count-raw process to correctly map features with associated feature symbols.

14.0.1 2018-10-23

Fixed
  • Handle missing gene expression in hierarchical clustering of genes. If one or more genes requested in gene filter are missing in selected expression files a warning is issued and hierarchical clustering of genes is computed with the rest of the genes instead of failing.
  • Fix PCA computation for single sample case

14.0.0 2018-10-09

Changed
  • BACKWARD INCOMPATIBLE: Require Resolwe 13.x
  • BACKWARD INCOMPATIBLE: Remove gsize input from macs2-callpeak process and automate genome size selection
  • BACKWARD INCOMPATIBLE: Set a new default sample and reads descriptor schema. Change slug from sample2 to sample, modify group names, add cell_type field to the new sample descriptor schema, and remove the original sample, sample-detailed, and reads-detailed descriptor schemas.
  • BACKWARD INCOMPATIBLE: Unify types of macs14 and macs2-callpeak processes and make rose2 work with both
  • BACKWARD INCOMPATIBLE: Remove replicates input in cuffnorm process. Use sample relation information instead.
  • Use resolwebio/chipseq:3.0.0 docker image in the following processes:
    • macs14
    • macs2-callpeak
    • rose2
  • Downgrade primerclip to old version (v171018) in resolwebio/dnaseq:3.3.0 docker image and move it to google drive.
  • Move bam-split process to resolwebio/rnaseq:3.7.1 docker image
  • Count unique and multimmaping reads in regtools-junctions-annotate process
Added
  • Add qc-prepeak process that reports ENCODE3 accepted ChIP-seq and ATAC-seq QC metrics
  • Add QC report to macs2-callpeak process
  • Add combining ChIP-seq QC reports in archive-samples process
  • Add detection of globin-derived reads as an additional QC step in the workflow-bbduk-star-featurecounts-qc-single and workflow-bbduk-star-featurecounts-qc-paired processes.
  • Add mappings from ENSEMBL or NCBI to UCSC chromosome names and deepTools (v3.1.0) to resolwebio/dnaseq:3.3.0 docker image
  • Add BigWig output field to following processors:
    • align-bwa-trim
    • upload-bam
    • upload-bam-indexed
    • upload-bam-secondary
  • Add replicate_groups Jinja expressions filter that accepts a list of data objects and returns a list of labels determining replicate groups.
  • Add ‘Novel splice junctions in BED format’ output to regtools-junctions-annotate process, so that user can visualize only novel splice juntions in genome browsers.
Fixed
  • Fix handling of numerical feature_ids (NCBI source) in create_expression_set.py script
  • Make chipseq-peakscore work with gzipped narrowPeak input from macs2-callpeak
  • Use uncompressed FASTQ files as input to STAR aligner to prevent issues on (network) filesystems without FIFO support

13.0.0 2018-09-18

Changed
  • BACKWARD INCOMPATIBLE: Require Resolwe 12.x
  • BACKWARD INCOMPATIBLE: Remove obsolete processes: assembler-abyss, cutadapt-amplicon, feature_location, microarray-affy-qc, reads-merge, reference_compatibility, transmart-expressions, upload-hmmer-db, upload-mappability-bigwig, upload-microarray-affy.
  • BACKWARD INCOMPATIBLE: Remove obsolete descriptor schema: transmart.
  • BACKWARD INCOMPATIBLE: Remove tools which are not used by any process: clustering_leaf_ordering.py, go_genesets.py, VCF_ad_extract.py, volcanoplot.py, xgff.py, xgtf2gff.py.
  • BACKWARD INCOMPATIBLE: Management command for inserting features and mappings requires PostgreSQL version 9.5 or newer
  • Update the meta data like name, description, category, etc. of most of the processes
  • Speed-up management command for inserting mappings
  • Change location of cufflinks to Google Drive for resolwebio/rnaseq Docker build
  • Calculate alignment statistics for the uploaded alignment (.bam) file in the upload-bam, upload-bam-indexed and upload-bam-secondary processes.
  • Annotation (GTF/GFF3) file input is now optional for the creation of the STAR genome index files. Annotation file can be used at the alignment stage to supplement the genome indices with the set of known features.
  • Trigger process warning instead of process error in the case when bamtobigwig.sh scripts detects an empty .bam file.
  • Set the default reads length filtering parameter to 30 bp in the rna-seq-bbduk-star-featurecounts and kapa-rna-seq-bbduk-star-featurecounts experiment descriptor schema. Expand the kit selection choice options in the latter descriptor schema.
Added
  • Add MultiQC (1.6.0) and Seqtk (1.2-r94) to the resolwebio/utils:1.5.0 Docker image
  • Add sample2 descriptor schema which is the successor of the original sample and reads descriptor schemas
  • Add bedToBigBed and Tabix to resolwebio/rnaseq:3.7.0 docker image
  • Add HS Panel choice option to the amplicon-master-file descriptor schema
  • Add MultiQC process
  • Add process for the Seqtk tool sample sub-command. This process allows sub-sampling of .fastq files using either a fixed number of reads or the ratio of the input file.
  • Add MultiQC analysis step to the workflow-bbduk-star-featurecounts-single and workflow-bbduk-star-featurecounts-single processes.
  • Add workflow-bbduk-star-featurecounts-qc-single and workflow-bbduk-star-featurecounts-qc-paired processes which support MultiQC analysis, input reads down-sampling (using Seqtk) and rRNA sequence detection using STAR aligner.
  • Add to resolwebio/chipseq Docker image:
    • bedtools (2.25.0-1)
    • gawk (1:4.1.3+dfsg-0.1)
    • picard-tools (1.113-2)
    • run_spp.R (1.2) (as spp)
    • SPP (1.14)
  • Add regtools-junctions-annotate process that annotates novel splice junctions.
  • Add background relation type to fixtures
Fixed
  • Track source information in the upload-fasta-nucl process.
  • When STAR aligner produces an empty alignment file, re-sort the alignment file to allow successful indexing of the output .bam file.
  • Create a symbolic link to the alignment file in the feature_counts process, so that relative path is used in the quantification results. This prevent the FeatureCounts output to be listed as a separate sample in the MultiQC reports.
  • Fix handling of expression objects in archive-samples process

12.0.0 - 2018-08-13

Changed
  • BACKWARD INCOMPATIBLE: Require Resolwe 11.x
  • BACKWARD INCOMPATIBLE: Use read count instead of sampling rate in strandedness detection
  • BACKWARD INCOMPATIBLE: Remove genome input from rose2 process and automate its selection
  • BACKWARD INCOMPATIBLE: Refactor cutadapt-paired process
  • BACKWARD INCOMPATIBLE: Improve leaf ordering performance in gene and sample hierarchical clustering. We now use exact leaf ordering which has been recently added to scipy instead of an approximate in-house solution based on nearest neighbor algorithm. Add informative warning and error messages to simplify troubleshooting with degenerate datasets.
  • Remove igvtools from resolwebio/utils Docker image
  • Improve helper text and labels in processes used for sequencing data upload
  • Allow using custom adapter sequences in the workflow-bbduk-star-featurecounts-single and workflow-bbduk-star-featurecounts-paired processes
  • Change chromosome names from ENSEMBL / NCBI to UCSC (example: “1” to “chr1”) in BigWig files. The purpose of this is to enable viewing BigWig files in UCSC genome browsers for files aligned with ENSEBML or NCBI genome. This change is done by adding script bigwig_chroms_to_ucsc.py to bamtobigwig.sh script.
  • Reduce RAM requirement in SRA import processes
Added
  • Add two-pass mode to alignment-star process
  • Add regtools (0.5.0) to resolwebio/rnaseq Docker image
  • Add KAPA experiment descriptor schema
  • Add resdk Python 3 package to resolwebio/utils Docker image
  • Add to cutadapt-single process an option to discard reads having more ‘N’ bases than specified.
  • Add workflows for single-end workflow-cutadapt-star-featurecounts-single and paired-end reads workflow-cutadapt-star-featurecounts-paired. Both workflows consist of preprocessing with Cutadapt, alignment with STAR two pass mode and quantification with featureCounts.
  • Add descriptor schema rna-seq-cutadapt-star-featurecounts
Fixed
  • BACKWARD INCOMPATIBLE: Fix the stitch parameter handling in rose2
  • fix upload-gtf to create JBrowse track only if GTF file is ok
  • Pin sra-toolkit version to 2.9.0 in resolwebio/utils Docker image.
  • Fix and improve rose2 error messages
  • Fail gracefully if bam file is empty when producing bigwig files
  • Fail gracefully if there are no matches when mapping chromosome names

11.0.0 - 2018-07-17

Changed
  • BACKWARD INCOMPATIBLE: Remove management command module
  • BACKWARD INCOMPATIBLE: Remove filtering of genes with low expression in PCA analysis
  • BACKWARD INCOMPATIBLE: Remove obsolete RNA-seq DSS process
  • Expand error messages in rose2 process
  • Check for errors during download of FASTQ files and use resolwebio/utils:1.3.0 Docker image in import SRA process
  • Increase Feature’s full name’s max length to 350 to support a long full name of “Complement C3 Complement C3 beta chain C3-beta-c Complement C3 alpha chain C3a anaphylatoxin Acylation stimulating protein Complement C3b alpha’ chain Complement C3c alpha’ chain fragment 1 Complement C3dg fragment Complement C3g fragment Complement C3d fragment Complement C3f fragment Complement C3c alpha’ chain fragment 2” in Ensembl
Added
  • Add exp_set and exp_set_json output fields to expression processes:
    • feature_counts
    • htseq-count
    • htseq-count-raw
    • rsem
    • upload-expression
    • upload-expression-cuffnorm
    • upload-expression-star
  • Add ‘Masking BED file’ input to rose2 process which allows masking reagions from the analysis
  • Add filtering.outFilterMismatchNoverReadLmax input to alignment-star process
  • Add mappings from ENSEMBL or NCBI to UCSC chromosome names to resolwebio/rnaseq:3.5.0 docker image
Fixed
  • Fix peaks BigBed output in macs14 process
  • Remove duplicated forward of alignIntronMax input field in BBDuk - STAR - featureCounts workflow
  • Make cuffnorm process attach correct expression data objects to samples
  • Fix upload-gtf in a way that GTF can be shown in JBrowse. Because JBrowse works only with GFF files, input GTF is converted to GFF from which JBrowse track is created.

10.0.1 - 2018-07-06

Fixed
  • Fix bamtobigwig.sh to timeout the bamCoverage calculation after defined time

10.0.0 - 2018-06-19

Added
  • Add to resolwebio/chipseq Docker image:
    • Bedops (v2.4.32)
    • Tabix (v1.8)
    • python3-pandas
    • bedGraphToBigWig (kent-v365)
    • bedToBigBed (kent-v365)
  • Add to resolwebio/rnaseq:3.2.0 Docker image:
    • genometools (1.5.9)
    • igvtools (v2.3.98)
    • jbrowse (v1.12.0)
    • Bowtie (v1.2.2)
    • Bowtie2 (v2.3.4.1)
    • BWA (0.7.17-r1188)
    • TopHat (v2.1.1)
    • Picard Tools (v2.18.5)
    • bedGraphToBigWig (kent-v365)
  • Add Debian package file to resolwebio/rnaseq:3.3.0 Docker image
  • Support filtering by type on feature API endpoint
  • Add BigWig output field to following processes:
    • alignment-bowtie
    • alignment-bowtie2
    • alignment-tophat2
    • alignment-bwa-mem
    • alignment-bwa-sw
    • alignment-bwa-aln
    • alignment-hisat2
    • alignment-star
  • Add Jbrowse track output field to upload-genome processor.
  • Use reslowebio/rnaseq Docker image and add Jbrowse track and IGV sorting and indexing to following processes:
    • upload-gff3
    • upload-gtf
    • gff-to-gtf
  • Add Tabix index for Jbrowse to upload-bed processor and use reslowebio/rnaseq Docker image
  • Add BigWig, BigBed and JBrowse track outputs to macs14 process
  • Add Species and Build outputs to rose2 process
  • Add Species, Build, BigWig, BigBed and JBrowse track outputs to macs2 process
  • Add scipy (v1.1.0) Python 3 package to resolwebio/utils Docker image
Changed

  • BACKWARD INCOMPATIBLE: Drop support for Python 3.4 and 3.5

  • BACKWARD INCOMPATIBLE: Require Resolwe 10.x

  • BACKWARD INCOMPATIBLE: Upgrade to Django Channels 2

  • BACKWARD INCOMPATIBLE: Count fragments (or templates) instead of reads by default in featureCounts process and BBDuk - STAR - featureCounts pipeline. The change applies only to paired-end data.

  • BACKWARD INCOMPATIBLE: Use resolwebio/rnaseq:3.2.0 Docker image in the following processes that output reads:

    • upload-fastq-single
    • upload-fastq-paired
    • files-to-fastq-single
    • files-to-fastq-paired
    • reads-merge
    • bbduk-single
    • bbduk-paired
    • cutadapt-single
    • cutadapt-paired
    • cutadapt-custom-single
    • cutadapt-custom-paired
    • trimmomatic-single
    • trimmomatic-paired.

    This change unifies the version of FastQC tool (0.11.7) used for quality control of reads in the aforementioned processes. The new Docker image comes with an updated version of Cutadapt (1.16) which affects the following processes:

    • cutadapt-single
    • cutadapt-paired
    • cutadapt-custom-single
    • cutadapt-custom-paired.

    The new Docker image includes also an updated version of Trimmomatic (0.36) used in the following processes:

    • upload-fastq-single
    • upload-fastq-paired
    • files-to-fastq-single
    • files-to-fastq-paired
    • trimmomatic-single
    • trimmomatic-paired.

  • BACKWARD INCOMPATIBLE: Change Docker image in alignment-subread from resolwebio/legacy:1.0.0 with Subread (v1.5.1) to resolwebio/rnaseq:3.2.0 with Subread (v1.6.0). --multiMapping option was added instead of --unique_reads. By default aligner report uniquely mapped reads only.

  • Update wigToBigWig to kent-v365 version in resolwebio/chipseq Docker image

  • Change paths in HTML amplicon report template in resolwebio/dnaseq Docker image

  • Move assay type input in BBDuk - STAR - featureCounts pipeline descriptor schema to advanced options

  • Use resolwebio/rnaseq:3.2.0 Docker image with updated versions of tools instead of resolwebio/legacy:1.0.0 Docker image in following processes:

    • alignment-bowtie with Bowtie (v1.2.2) instead of Bowtie (v1.1.2)
    • alignment-bowtie2 with Bowtie2 (v2.3.4.1) instead of Bowtie2 (v2.2.6)
    • alignment-tophat2 with TopHat (v2.1.1) instead of TopHat (v2.1.0)
    • alignment-bwa-mem, alignment-bwa-sw` and ``alignment-bwa-aln with BWA (v0.7.17-r1188) instead of BWA (v0.7.12-r1039)
    • alignment-hisat2 with HISAT2 (v2.1.0) instead of HISAT2 (v2.0.3-beta)
    • upload-genome

  • Use resolwebio/base:ubuntu-18.04 Docker image as a base image in resolwebio/utils Docker image

  • Update Python 3 packages in resolwebio/utils Docker image:

    • numpy (v1.14.4)
    • pandas (v0.23.0)

  • Replace bedgraphtobigwig with deepTools in resolwebio/rnaseq Docker image, due to faster performance

  • Use resolwebio/rnaseq:3.3.0 Docker image in alignment-star-index with STAR (v2.5.4b)

Fixed
  • Make management commands use a private random generator instance
  • Fix output covplot_html of coveragebed process
  • Fix process archive-samples and amplicon-archive-multi-report to correctly handle nested file paths
  • Change rose2 and chipseq-peakscore to work with .bed or .bed.gz input files
  • Fix the expression-aggregator process so that it tracks the species of the input expression data
  • Fix bamtobigwig.sh to use deepTools instead of bedtools with bedgraphToBigWig due to better time performance

9.0.0 - 2018-05-15

Changed
  • BACKWARD INCOMPATIBLE: Simplify the amplicon-report process inputs by using Latex report template from the resolwebio/latex Docker image assets
  • BACKWARD INCOMPATIBLE: Simplify the coveragebed process inputs by using Bokeh assets from the resolwebio/dnaseq Docker image
  • BACKWARD INCOMPATIBLE: Require Resolwe 9.x
  • Update wigToBigWig tool in resolwebio/chipseq Docker image
  • Use resolwebio/rnaseq:3.1.0 Docker image in the following processes:
    • cufflinks
    • cuffnorm
    • cuffquant
  • Remove differentialexpression-limma process
  • Use resolwebio/rnaseq:3.1.0 docker image and expand error messages in:
    • cuffdiff
    • differentialexpression-deseq2
    • differentialexpression-edger
  • Update workflow-bbduk-star-htseq
  • Update quantseq descriptor schema
  • Assert species and build in htseq-count-normalized process
  • Set amplicon report template in resolwebio/latex Docker image to landscape mode
Added
  • Support Python 3.6
  • Add template_amplicon_report.tex to resolwebio/latex Docker image assets
  • Add SnpEff tool and bokeh assets to resolwebio/dnaseq Docker image
  • Add automated library strand detection to feature_counts quantification process
  • Add FastQC option nogroup to bbduk-single and bbduk-paired processes
  • Add CPM normalization to htseq-count-raw process
  • Add workflow-bbduk-star-htseq-paired
  • Add legend to amplicon report template in resolwebio/latex Docker image
Fixed
  • Fix manual installation of packages in Docker images to handle dots and spaces in file names correctly
  • Fix COSMIC url template in amplicon-table process
  • Fix Create IGV session in Archive samples process
  • Fix source tracking in cufflinks and cuffquant processes
  • Fix amplicon master file validation script. Check and report error if duplicated amplicon names are included. Validation will now pass also for primer sequences in lowercase.
  • Fix allele frequency (AF) calculation in snpeff process
  • Fix bug in script for calculating FPKM. Because genes of raw counts from featureCounts were not lexicographically sorted, division of normalized counts was done with values from other, incorrect, genes. Results from featureCounts, but not HTSeq-count process, were affected.

8.1.0 - 2018-04-13

Changed
  • Use the latest versions of the following Python packages in resolwebio/rnaseq docker image: Cutadapt 1.16, Apache Arrow 0.9.0, pysam 0.14.1, requests 2.18.4, appdirs 1.4.3, wrapt 1.10.11, PyYAML 3.12
  • Bump tools version in resolwebio/rnaseq docker image:
    • Salmon to 0.9.1
    • FastQC to 0.11.7
  • Generalize the no-extraction-needed use-case in resolwebio/base Docker image download_and_verify script
Added
  • Add the following Python packages to resolwebio/rnaseq docker image: six 1.11.0, chardet 3.0.4, urllib3 1.22, idna 2.6, and certifi 2018.1.18
  • Add edgeR R library to resolwebio/rnaseq docker image
  • Add Bedtools to resolwebio/rnaseq docker image
Fixed
  • Handle filenames with spaces in the following processes:
    • alignment-star-index
    • alignment-tophat2
    • cuffmerge
    • index-fasta-nucl
    • upload-fasta-nucl
  • Fix COSMIC url template in (multisample) amplicon reports

8.0.0 - 2018-04-11

Changed
  • BACKWARD INCOMPATIBLE: Refactor trimmomatic-single, trimmomatic-paired, bbduk-single, and bbduk-paired processes
  • BACKWARD INCOMPATIBLE: Merge align-bwa-trim and align-bwa-trim2 process functionality. Retain only the refactored process under slug align-bwa-trim
  • BACKWARD INCOMPATIBLE: In processes handling VCF files, the output VCF files are stored in bgzip-compressed form. Tabix index is not referenced to an original VCF file anymore, but stored in a separate tbi output field
  • BACKWARD INCOMPATIBLE: Remove an obsolete workflow-accel-2 workflow
  • BACKWARD INCOMPATIBLE: Use Elasticsearch version 5.x
  • BACKWARD INCOMPATIBLE: Parallelize execution of the following processes:
    • alignment-bowtie2
    • alignment-bwa-mem
    • alignment-hisat2
    • alignment-star
    • alignment-tophat2
    • cuffdiff
    • cufflinks
    • cuffquant
  • Require Resolwe 8.x
  • Bump STAR aligner version in resolwebio/rnaseq docker image to 2.5.4b
  • Bump Primerclip version in resolwebio/dnaseq docker image
  • Use resolwebio/dnaseq Docker image in picard-pcrmetrics process
  • Run vc-realign-recalibrate process using multiple cpu cores to optimize the processing time
  • Use resolwebio/rnaseq Docker image in alignment-star process
Added
  • Add CNVKit, LoFreq and GATK to resolwebio/dnaseq docker image
  • Add BaseSpace files download tool
  • Add process to import a file from BaseSpace
  • Add process to convert files to single-end reads
  • Add process to convert files to paired-end reads
  • Add vc-gatk4-hc process which implements GATK4 HaplotypeCaller variant calling tool
  • Add workflow-accel-gatk4 pipeline that uses GATK4 HaplotypeCaller as an alternative to GATK3 used in workflow-accel pipeline
  • Add amplicon-master-file descriptor schema
  • Add workflow-bbduk-star-featurecounts pipeline
  • Add rna-seq-bbduk-star-featurecounts RNA-seq descriptor schema
Fixed
  • Fix iterative trimming in bowtie and bowtie2 processes
  • Fix archive-samples to use sample names for headers when merging expressions
  • Improve goea.py tool to handle duplicated mapping results
  • Handle filenames with spaces in the following processes:
    • alignment-hisat2
    • alignment-bowtie
    • prepare-geo-chipseq
    • prepare-geo-rnaseq
    • cufflinks
    • cuffquant

7.0.1 - 2018-03-27

Fixed
  • Use name-ordered BAM file for counting reads in HTSeq-count process by default to avoid buffer overflow with large BAM files

7.0.0 - 2018-03-13

Changed
  • BACKWARD INCOMPATIBLE: Remove Ubuntu 17.04 base Docker image since it has has reached its end of life and change all images to use the new ubuntu 17.10 base image
  • BACKWARD INCOMPATIBLE: Require species and build inputs in the following processes:
    • upload-genome
    • upload-gtf
    • upload-gff3
    • upload-bam
    • upload-bam-indexed
  • BACKWARD INCOMPATIBLE: Track species and build information in the following processes:
    • cuffmerge
    • alignment processes
    • variant calling processes
    • JBrowse processes
  • BACKWARD INCOMPATIBLE: Track species, build and feature_type in the following processes:
    • upload-expression-star
    • quantification processes
    • differential expression processes
  • BACKWARD INCOMPATIBLE: Track species in gene set (Venn) and goenrichment processes
  • BACKWARD INCOMPATIBLE: Rename genes_source input to source in hierarchical clustering and PCA processes
  • BACKWARD INCOMPATIBLE: Remove the following obsolete processes:
    • Dictyostelium-specific ncRNA quantification
    • go-geneset
    • bayseq differential expression
    • cuffmerge-gtf-to-gff3
    • transdecoder
    • web-gtf-dictybase
    • upload-rmsk
    • snpdat
  • BACKWARD INCOMPATIBLE: Unify output fields of processes of type data:annotation
  • BACKWARD INCOMPATIBLE: Rename the organism field names to species in rna-seq and cutadapt-star-htseq descriptor schemas
  • BACKWARD INCOMPATIBLE: Rename the genome_and_annotation field name to species in bcm-* descriptor schemas and use the full species name for the species field values
  • BACKWARD INCOMPATIBLE: Refactor featureCounts process
  • BACKWARD INCOMPATIBLE: Change import-sra process to work with resolwebio/utils Docker image and refactor its inputs
  • Require Resolwe 7.x
  • Add environment export for Jenkins so that the manager will use a globally-unique channel name
  • Set scheduling_class of gene and sample hierarchical clustering processes to interactive
  • Change base Docker images of resolwebio/rnaseq and resolwebio/dnaseq to resolwebio/base:ubuntu-18.04
  • Use the latest versions of the following Python packages in resolwebio/rnaseq Docker image: Cutadapt 1.15, Apache Arrow 0.8.0, pysam 0.13, and xopen 0.3.2
  • Use the latest versions of the following Python packages in resolwebio/dnaseq Docker image: Bokeh 0.12.13, pandas 0.22.0, Matplotlib 2.1.2, six 1.11.0, PyYAML 3.12, Jinja2 2.10, NumPy 1.14.0, Tornado 4.5.3, and pytz 2017.3
  • Use the latest version of wigToBigWig tool in resolwebio/chipseq Docker image
  • Use resolwebio/rnaseq:3.0.0 Docker image in goenrichment, upload-gaf and upload-obo processes
  • Use resolwebio/dnaseq:3.0.0 Docker image in filtering_chemut process
  • Change cuffnorm process type to data:cuffnorm
  • Set type of coverage-garvan process to data:exomecoverage
  • Remove gsize input from macs14 process and automate genome size selection
  • Adjust bam-split process so it can be included in workflows
  • Make ID attribute labels in featureCounts more informative
  • Change ‘source’ to ‘gene ID database’ in labes and descriptions
  • Change archive-samples process to create different IGV session files for build and species
  • Expose advanced parameters in Chemical Mutagenesis workflow
  • Clarify some descriptions in the filtering_chemut process and chemut workflow
  • Change expected genome build formatting for hybrid genomes in bam-split process
  • Set the cooksCutoff parameter to FALSE in deseq.R tool
  • Rename ‘Expressions (BCM)’ to ‘Dicty expressions’
Added
  • Mechanism to override the manager’s control channel prefix from the environment
  • Add Ubuntu 17.10 and Ubuntu 18.04 base Docker images
  • Add resolwebio/utils Docker image
  • Add BBMap, Trimmomatic, Subread, Salmon, and dexseq_prepare_annotation2 tools and DEXSeq and loadSubread R libraries to resolwebio/rnaseq Docker image
  • Add abstract processes that ensure that all processes that inherit from them have the input and output fields that are defined in them:
    • abstract-alignment
    • abstract-annotation
    • abstract-expression
    • abstract-differentialexpression
    • abstract-bed
  • Add miRNA workflow
  • Add prepare-geo-chipseq and prepare-geo-rnaseq processes that produce a tarball with necessary data and folder structure for GEO upload
  • Add library-strandedness process which uses the Salmon tool built-in functionality to detect the library strandedness information
  • Add species and genome build output fields to macs14 process
  • Expose additional parameters in alignment-star, cutadapt-single and cutadapt-paired processes
  • Add merge expressions to archive-samples process
  • Add description of batch mode to Expression aggregator process
  • Add error and warning messages to the cuffnorm process
  • Add optional species input to hierarchical clustering and PCA processes
  • Add Rattus norvegicus species choice to the rna-seq descriptor schema to allow running RNA-seq workflow for this species from the Recipes
Fixed
  • Fix custom argument passing script for Trimmomatic in resolwebio/rnaseq Docker image
  • Fix installation errors for dexseq-prepare-annotation2 in resolwebio/rnaseq Docker image
  • Fix consensus_subreads input option in Subread process
  • Limit variant-calling process in the chemical mutagenesis workflow and the Picard tools run inside to 16 GB of memory to prevent them from crashing because they try to use too much memory
  • The chemical mutagenesis workflow was erroneously categorized as data:workflow:rnaseq:cuffquant type. This is switched to data:workflow:chemut type.
  • Fix handling of NA values in Differential expression results table. NA values were incorrectly replaced with value 0 instead of 1
  • Fix cuffnorm process to work with samples containing dashes in their name and dispense prefixing sample names starting with numbers with ‘X’ in the cuffnorm normalization outputs
  • Fix cuffnorm process’ outputs to correctly track species and build information
  • Fix typos and sync parameter description common to featureCounts and miRNA workflow

6.2.2 - 2018-02-21

Fixed
  • Fix cuffnorm process to correctly use sample names as labels in output files and expand cuffnorm tests

6.2.1 - 2018-01-28

Changed
  • Update description text of cutadapt-star-htseq descriptor schema to better describe the difference between gene/transcript-type analyses
  • Speed-up management command for inserting mappings

6.2.0 - 2018-01-17

Added
  • Add R, tabix, and CheMut R library to resolwebio/dnaseq Docker image
  • Add SRA Toolkit to resolwebio/rnaseq Docker image
Changed
  • Require Resolwe 6.x
  • Extend pathway map with species and source field
  • Move template and logo for multi-sample report into resolwebio/latex Docker image
  • Refactor amplicon-report process to contain all relevant inputs for amplicon-archive-multi-report
  • Refactor amplicon-archive-multi-report
  • Use resolwebio/dnaseq:1.2.0 Docker image in filtering_chemut process
Fixed
  • Enable DEBUG setting in tests using Django’s LiveServerTestCase
  • Wait for ElasticSeach to index the data in KBBioProcessTestCase
  • Remove unused parameters in TopHat (2.0.13) process and Chip-seq workflow

6.1.0 - 2017-12-12

Added
  • Add amplicon-archive-multi-report process
  • Add upload-metabolic-pathway process
  • Add memory-optimized primerclip as a separate align-bwa-trim2 process
  • Add workflow-accel-2 workflow
Changed
  • Improve PCA process performance
  • Use resolwebio/chipseq:1.1.0 Docker image in macs14 process
  • Change formatting of EFF[*].AA column in snpeff process
  • Save unmapped reads in aligment-hisat2 process
  • Turn off test profiling
Fixed
  • Fix pre-sorting in upload-master-file process
  • Revert align-bwa-trim process to use non-memory-optimized primerclip
  • Fix file processing in cutadapt-custom-paired process

6.0.0 - 2017-11-28

Added
  • Add AF filter to amplicon report
  • Add number of samples to the output of expression aggregator
  • Add ChIP-Rx, ChIPmentation and eClIP experiment types to reads descriptor schema
  • Add pandas Python package to resolwebio/latex Docker image
  • Add primerclip, samtools, picard-tools and bwa to resolwebio/dnaseq Docker image
  • Add cufflinks, RNASeqT R library, pyarrow and sklearn Python packages to resolwebio/rnaseq Docker image
  • Add wigToBigWig tool to resolwebio/chipseq Docker image
Changed
  • BACKWARD INCOMPATIBLE: Drop Python 2 support, require Python 3.4 or 3.5
  • BACKWARD INCOMPATIBLE: Make species part of the feature primary key
  • BACKWARD INCOMPATIBLE: Substitute Python 2 with Python 3 in resolwebio/rnaseq Docker image. The processes to be updated to this version of the Docker image should also have their Python scripts updated to Python 3.
  • Require Resolwe 5.x
  • Set maximum RAM requirement in bbduk process
  • Move Assay type input parameter in RNA-Seq descriptor schema from advanced options to regular options
  • Use resolwebio/rnaseq Docker image in Cutadapt processes
  • Use additional adapter trimming option in cutadapt-custom-single/paired processes
  • Show antibody information in reads descriptor for ChIP-Seq, ChIPmentation, ChIP-Rx, eClIP, MNase-Seq, MeDIP-Seq, RIP-Seq and ChIA-PET experiment types
  • Use resolwebio/dnaseq Docker image in align-bwa-trim process
  • Refactor resolwebio/chipseq Docker image
  • Use Resolwe’s Test Runner for running tests and add ability to only run a partial test suite based on what proceses have Changed
  • Configure Jenkins to only run a partial test suite when testing a pull request
  • Make tests use the live Resolwe API host instead of external server
Fixed
  • Fix merging multiple expressions in DESeq process
  • Fix resolwebio/rnaseq Docker image’s README
  • Handle multiple ALT values in amplicon report
  • Fix BAM file input in rsem process

5.0.1 - 2017-11-14

Fixed
  • Update Features and Mappings ElasticSearch indices building to be compatible with Resolwe 4.0

5.0.0 - 2017-10-25

Added
  • Add automatic headers extractor to bam-split process
  • Add HTML amplicon plot in coveragebed process
  • Add raw RSEM tool output to rsem process output
  • Add support for transcript-level differential expression in deseq2 process
Changed
  • BACKWARD INCOMPATIBLE: Bump Django requirement to version 1.11.x
  • BACKWARD INCOMPATIBLE: Make BioProcessTestCase non-transactional
  • Require Resolwe 4.x
  • Add the advanced options checkbox to the rna-seq descriptor schema
  • Remove static amplicon plot from coveragebed and amplicon-report processes
  • Update Dockerfile for resolwebio/latex with newer syntax and add some additional Python packages

4.2.0 - 2017-10-05

Added
  • Add resolwebio/base Docker image based on Ubuntu 17.04
  • Add resolwebio/dnaseq Docker image
  • Add DESeq2 tool to resolwebio/rnaseq docker image
  • Add input filename regex validator for upload-master-file process
Changed
  • Remove obsolete mongokey escape functionality
  • Report novel splice-site junctions in HISAT2
  • Use the latest stable versions of the following bioinformatics tools in resolwebio/rnaseq docker image: Cutadapt 1.14, FastQC 0.11.5, HTSeq 0.9.1, and SAMtools 1.5

4.1.0 - 2017-09-22

Added
  • Add Mus musculus to all BCM workflows’ schemas
  • Add bam-split process with supporting processes upload-bam-primary, upload-bam-secondary and upload-header-sam
Changed
  • Enable Chemut workflow and process tests
Fixed
  • Fix chemut intervals input option

4.0.0 - 2017-09-14

Added
  • New base and legacy Docker images for processes, which support non-root execution as implemented by Resolwe
Changed
  • BACKWARD INCOMPATIBLE: Modify all processes to explicitly use the new Docker images
  • BACKWARD INCOMPATIBLE: Remove clustering-hierarchical-genes-etc process
  • Require Resolwe 3.x

3.2.0 2017-09-13

Added
  • Add index-fasta-nucl and rsem process
  • Add custom Cutadapt - STAR - RSEM workflow

3.1.0 2017-09-13

Added
  • Add statistics of logarithmized expressions to expression-aggregator
  • Add input field description to cutadapt-star-htseq descriptor schema
  • Add HISAT2 and RSEM tool to resolwebio/rnaseq docker image
Changed
  • Remove eXpress tool from resolwebio/rnaseq docker image
  • Use system packages of RNA-seq tools in resolwebio/rnaseq docker image
  • Set hisat2 process’ memory resource requirement to 32GB
  • Use resolwebio/rnaseq docker image in hisat2 process

3.0.0 2017-09-07

Added
  • Add custom Cutadapt - STAR - HT-seq workflow
  • Add expression aggregator process
  • Add resolwebio/rnaseq docker image
  • Add resolwebio/latex docker image
  • Add access to sample field of data objects in processes via sample filter
Changed
  • BACKWARD INCOMPATIBLE: Remove threads input in STAR aligner process and replace it with the cores resources requirement
  • BACKWARD INCOMPATIBLE: Allow upload of custom amplicon master files (make changes to amplicon-panel descriptor schema, upload-master-file and amplicon-report processes and workflow-accel workflow)
  • BACKWARD INCOMPATIBLE: Remove threads input in cuffnorm process and replace it with the cores resources requirement
  • Add sample descriptor to prepare_expression test function
  • Prettify amplicon report
Fixed
  • Fix upload-expression-star process to work with arbitrary file names
  • Fix STAR aligner to work with arbitrary file names
  • Fix cuffnorm group analysis to work correctly
  • Do not crop Amplicon report title as this may result in malformed LaTeX command
  • Escape LaTeX’s special characters in make_report.py tool
  • Fix validation error in Test sleep progress process

2.0.0 2017-08-25

Added
  • Support bioinformatics process test case based on Resolwe’s TransactionProcessTestCase
  • Custom version of Resolwe’s with_resolwe_host test decorator which skips the decorated tests on non-Linux systems
  • Add optimal leaf ordering and simulated annealing to gene and sample hierarchical clustering
  • Add resolwebio/chipseq docker image and use it in ChIP-Seq processes
  • Add Odocoileus virginianus texanus (deer) organism to sample descriptor
  • Add test for import-sra process
  • Add RNA-seq DSS test
  • Add Cutadapt and custom Cutadapt processes
Changed
  • Require Resolwe 2.0.x
  • Update processes to support new input sanitization introduced in Resolwe 2.0.0
  • Improve variant table name in amplicon report
  • Prepend api/ to all URL patterns in the Django test project
  • Set hisat2 process’ memory resource requirement to 16GB and cores resource requirement to 1
  • Filter LoFreq output VCF files to remove overlapping indels
  • Add Non-canonical splice sites penalty, Disallow soft clipping and Report alignments tailored specifically for Cufflinks parameters to hisat2 process
  • Remove threads input from cuffquant and rna-seq workfows
  • Set core resource requirement in cuffquant process to 1
Fixed
  • Correctly handle paired-end parameters in featureCount
  • Fix NaN in explained variance in PCA. When PC1 alone explained more than 99% of variance, explained variance for PC2 was not returned
  • Fix input sanitization error in dss-rna-seq process
  • Fix gene source check in hierarchical clustering and PCA
  • Enable network access for all import processes
  • Fix RNA-seq DSS adapters bug
  • Fix sample hierarchical clustering output for a single sample case

1.4.1 2017-07-20

Changed
  • Optionally report all amplicons in Amplicon table
Fixed
  • Remove remaining references to calling pip with --process-dependency-links argument

1.4.0 2017-07-04

Added
  • Amplicon workflow
  • Amplicon descriptor schemas
  • Amplicon report generator
  • Add Rattus norvegicus organism choice to sample schema
  • Transforming form Phred 64 to Phred 33 when uploading fastq reads
  • Add primertrim process
  • RNA-Seq experiment descriptor schema
  • iCount sample and reads descriptor schemas
  • iCount demultiplexing and sample annotation
  • ICount QC
  • Add MM8, RN4 and RN6 options to rose2 process
  • Add RN4 and RN6 options to bamplot process
  • Archive-samples process
  • Add bamliquidator
  • CheMut workflow
  • Dicty primary analysis descriptor schema
  • IGV session to Archive-samples process
  • Use Resolwe’s field projection mixins for knowledge base endpoints
  • amplicon-table process
  • Add C. griseus organism choice to Sample descriptor schema
  • Add S. tuberosum organism choice to Sample descriptor schema
  • Add log2 to gene and sample hierarchical clustering
  • Add new inputs to import SRA, add read type selection process
  • Set memory resource requirement in jbrowse annotation gff3 and gtf processes to 16GB
  • Set memory resource requirement in star alignment and index processes to 32GB
  • Add C. elegans organism choice to Sample descriptor schema
  • Add D. melanogaster organism choice to Sample descriptor schema
  • Set core resource requirement in Bowtie process to 1
  • Set memory resource requirement in amplicon BWA trim process to 32GB
  • Add new master file choices to amplicon panel descriptor schema
  • Add S. tuberosum organism choice to RNA-seq workflow
  • Add Cutadapt process
  • Add leaf ordering to gene and sample hierarchical clustering
Fixed
  • Use new import paths in resolwe.flow
  • Upload reads (paired/single) containing whitespace in the file name
  • Fix reads filtering processes for cases where input read file names contain whitespace
  • Add additional filtering option to STAR aligner
  • Fix bbduk-star-htseq_count workflow
  • Fix cuffnorm process: Use sample names as labels (boxplot, tables), remove group labels input, auto assign group labels, add outputs for Rscript output files which were only available compressed
  • Derive output filenames in hisat2 from the first reads filename
  • Correctly fetch KB features in goea.py
  • Append JBrowse tracks to sample
  • Replace the BAM MD tag in align-bwa-trim process to correct for an issue with the primerclip tool
  • Fix typo in trimmomatic and bbduk processes
  • Use re-import in etc and hmmer_database processes
Changed
  • Support Resolwe test framework
  • Run tests in parallel with Tox
  • Use Resolwe’s new FLOW_DOCKER_COMMAND setting in test project
  • Always run Tox’s docs, linters and packaging environments with Python 3
  • Add extra Tox testing environment with a check that there are no large test files in resolwe_bio/tests/files
  • Replace Travis CI with Genialis’ Jenkins for running the tests
  • Store compressed and uncompressed .fasta files in data:genome:fasta objects
  • Change sample_geo descriptor schema to have strain option available for all organisms
  • More readable rna-seq-quantseq schema, field stranded
  • Remove obsolete Gene Info processes
  • Change log2(fc) default from 2 to 1 in diffexp descriptor schema
  • Change Efective genome size values to actual values in macs14 process
  • Change variable names in bowtie processes
  • Remove iClip processes, tools, files and tests

1.3.0 2017-01-28

Changed
  • Add option to save expression JSON to file before saving it to Storage
  • Update upload-expression process
  • No longer treat resolwe_bio/tools as a Python package
  • Move processes’ test files to the resolwe_bio/tests/files directory to generalize and simplify handling of tests’ files
  • Update differential expression (DE) processors
  • Update generate_diffexpr_cuffdiff django-admin command
  • Save gene_id source to output.source for DE, expression and related objects
  • Refactor upload-diffexp processor
  • Update sample descriptor schema
  • Remove obsolete descriptor schemas
  • Add stitch parameter to rose2 processor
  • Add filtering to DESeq2
  • Set Docker Compose’s project name to resolwebio to avoid name clashes
  • GO enrichment analysis: map features using gene Knowledge base
  • Add option to upload .gff v2 files with upload-gtf processor
  • Replace Haystack with Resolwe Elastic Search API
  • Require Resolwe 1.4.1+
  • Update processes to be compatible with Resolwe 1.4.0
Added
  • Process definition documentation style and text improvements
  • Add resolwe_bio.kb app, Resolwe Bioinformatics Knowledge Base
  • Add tests to ensure generators produce the same results
  • Upload Gene sets (data:geneset)
  • Add generate_geneset django-admin command
  • Add generate_diffexpr_deseq django-admin command
  • Add ‘Generate GO gene sets’ processor
  • Add generic file upload processors
  • Add upload processor for common image file types (.jpg/.tiff/.png/.gif)
  • Add upload processor for tabular file formats (.tab/.tsv/.csv/.txt/.xls/.xlsx)
  • Add Trimmomatic process
  • Add featureCounts process
  • Add Subread process
  • Add process for hierarchical clusteing of samples
  • Add gff3 to gtf file converter
  • Add microarray data descriptor schema
  • Add process for differential expression edgeR
  • BioCollectionFilter and BidDataFilter to support filtering collections and data by samples on API
  • Added processes for automatically downloading single and paired end SRA files from NCBI and converting them to FASTQ
  • Added process for automatically downloading SRA files from NCBI and converting them to FASTQ
  • Add HEAT-Seq pipeline tools
  • Add HEAT-Seq workflow
  • Add create-geneset, create-geneset-venn processors
  • Add source filter to feature search endpoint
  • Add bamplot process
  • Add gene hiererhical clustering
  • Add cuffquant workflow
  • Support Django 1.10 and versionfield 0.5.0
  • django-admin commands insert_features and insert_mappings for importing features and mappings to the Knowledge Base
  • Add bsmap and mcall to analyse WGBS data
  • Vaccinesurvey sample descriptor schema
  • Add RNA-Seq single and paired-end workflow
Fixed
  • Set presample to False for Samples created on Sample endpoint
  • Fix FastQC report paths in processors
  • Fix htseq_count and featureCounts for large files
  • Fix upload gtf annotation
  • Fix gene_id field type for differential expression storage objects
  • Order data objects in SampleViewSet
  • Fix sample hiererhical clustering
  • Fix name in gff to gtf process
  • Fix clustering to read expressed genes as strings
  • Fix protocol labels in rna-seq-quantseq descriptor schema

1.2.1 2016-07-27

Changed
  • Update resolwe requirement

1.2.0 2016-07-27

Changed
  • Decorate all tests that currently fail on Docker with skipDockerFailure
  • Require Resolwe’s master git branch
  • Put packaging tests in a separate Tox testing environment
  • Rename DB user in test project
  • Change PostgreSQL port in test project
  • Add ROSE2 results parser
  • Compute index for HISAT2 aligner on genome upload
  • Updated Cuffquant/Cuffnorm tools
  • Change ROSE2 enhancer rank plot labels
  • Refactor processor syntax
  • Move processes tests into processes subdirectory
  • Split sample API endpoint to sample for annotated Samples and presample for unannotated Samples
  • Rename test project’s data and upload directories to .test_data and .test_upload
  • Save fastq files to lists:basic:file field. Refactor related processors.
  • Reference genome-index path when running aligners.
  • Add pre-computed genome-index files when uploading reference fasta file.
  • Include all necessary files for running the tests in source distribution
  • Exclude tests from built/installed version of the package
  • Move testing utilities from resolwe_bio.tests.processes.utils to resolwe_bio.utils.test
  • Update Cuffdiff processor inputs and results table parsing
  • Refactor processes to use the updated resolwe.flow.executors.run command
  • Refactor STAR aligner - export expressions as separate objects
Fixed
  • Make Tox configuration more robust to different developer environments
  • Set required: false in processor input/output fields where necessary
  • Add Sample’s Data objects to Collection when Sample is added
  • Fixed/renamed Cufflinks processor field names
Added
  • skipDockerFailure test decorator
  • Expand documentation on running tests
  • Use Travis CI to run the tests
  • Add Sample model and corresponding viewset and filter
  • Add docker-compose command for PostgreSQL
  • API endpoint for adding Samples to Collections
  • HISAT2 aligner
  • Use Git Large File Storage (LFS) for large test files
  • Test for generate_samples django-admin command
  • django-admin command: generate_diffexpr

1.1.0 2016-04-18

Changed
  • Remove obsolete utilities superseded by resolwe-runtime-utils
  • Require Resolwe 1.1.0
Fixed
  • Update sample descriptor schema
  • Include all source files and supplementary package data in sdist
Added
  • flow_collection: sample to processes
  • MACS14 processor
  • Initial Tox configuration for running the tests
  • Tox tests for ensuring high-quality Python packaging
  • ROSE2 processor
  • django-admin command: generate_samples

1.0.0 2016-03-31

Changed
  • Renamed assertFileExist to assertFileExists
  • Restructured processes folder hierarchy
  • Removed re-require and hard-coded tools’ paths
Fixed
  • Different line endings are correctly handled when opening gzipped files
  • Fail gracefully if the field does not exist in assertFileExists
  • Enabled processor tests (GO, Expression, Variant Calling)
  • Enabled processor test (Upload reads with old Illumina QC encoding)
  • Made Resolwe Bioinformatics work with Resolwe and Docker
Added
  • Import expressions from tranSMART
  • Limma differential expression (tranSMART)
  • VC filtering tool (Chemical mutagenesis)
  • Additional analysis options to Abyss assembler
  • API endpoint for Sample
  • Initial documentation

Contributing

Installing prerequisites

Make sure you have Python 3.6 installed on your system. If you don’t have it yet, follow these instructions.

Resolwe Bioinformatics requires PostgreSQL (9.4+). Many Linux distributions already include the required version of PostgreSQL (e.g. Fedora 22+, Debian 8+, Ubuntu 15.04+) and you can simply install it via distribution’s package manager. Otherwise, follow these instructions.

The pip tool will install all Resolwe Bioinformatics’ dependencies from PyPI. Installing some (indirect) dependencies from PyPI will require having a C compiler (e.g. GCC) as well as Python development files installed on the system.

Note

The preferred way to install the C compiler and Python development files is to use your distribution’s packages, if they exist. For example, on a Fedora/RHEL-based system, that would mean installing gcc and python3-devel packages.

Optional prerequisites

If you want to run or develop tests with large input or output files, then install the Git Large File Storage extension.

Preparing environment

Fork the main Resolwe Bioinformatics’ git repository.

If you don’t have Git installed on your system, follow these instructions.

Clone your fork (replace <username> with your GitHub account name) and change directory:

git clone https://github.com/<username>/resolwe-bio.git
cd resolwe-bio

Prepare Resolwe Bioinformatics for development:

pip install --pre -e .[docs,package,test]

Note

We recommend using pyvenv to create an isolated Python environment for Resolwe Bioinformatics.

Preparing database

Add a postgres user:

createuser -s -r postgres

Running tests

Manually

Change directory to the tests Django project:

cd tests

Run docker:

docker-compose up

Note

On Mac or Windows, Docker might complain about non-mounted volumes. You can edit volumes in Docker => Preferences => File Sharing The following volumes need to be shared:

  • /private
  • /tmp
  • /var/folders

/private is shared by default. When you attempt to add /var/folders it might try to add /private/var/folders which will cause Docker complaining about overlapping volumes. Here’s a workaround: Change /private to /var/folders and then add /private again.

To run the tests, use:

./manage.py test resolwe_bio --parallel 2

Note

If you don’t specify the number of parallel test processes (i.e. you just use --parallel), Django will run one test process per each core available on the machine.

Warning

If you run Docker in a virtual machine (i.e. if you use MacOS or Windows) rather that directly on your machine, the virtual machine can become totally unresponsive if you set the number of parallel test processes too high. We recommend using at most --parallel 2 in such cases.

To run a specific test, use:

./manage.py test resolwe_bio.tests.<module-name>.<class-name>.<method-name>

For example, to run the test_macs14 test of the ChipSeqProcessorTestCase class in the test_chipseq module, use:

./manage.py test resolwe_bio.tests.processes.test_chipseq.ChipSeqProcessorTestCase.test_macs14
Using Tox

To run the tests with Tox, use:

tox

To re-create the virtual environment before running the tests, use:

tox -r

To only run the tests with a specific Python version, use:

tox -e py<python-version>

For example, to only run the tests with Python 3.5, use

tox -e py35

Note

To see the list of available Python versions, see tox.ini.

Note

To control the number of test processes Django will run in parallel, set the DJANGO_TEST_PROCESSES environment variable.

Since running tests for all processes may take a long time, there is an option to run partial tests based on what files have been changed between HEAD and a specific commit (e.g. master). The Tox environments that run partial tests have the -partial suffix, e.g.:

tox -e py35-partial

To configure the commit against which the changes are compared you should set the RESOLWE_TEST_ONLY_CHANGES_TO environmental variable (it is set to master by default).

Running tests skipped on Docker

To run the tests that are skipped on Docker due to failures and errors, set the RESOLWEBIO_TESTS_SKIP_DOCKER_FAILURES environment variable to no.

For example, to run the skipped tests during a single test run, use:

RESOLWEBIO_TESTS_SKIP_DOCKER_FAILURES=no ./manage.py test resolwe_bio

To run the skipped tests for the whole terminal session, execute:

export RESOLWEBIO_TESTS_SKIP_DOCKER_FAILURES=no

and then run the tests as usual.

Running tests with large files

To run the tests with large input or output files, ensure you have the Git Large File Storage extension installed and run the tests as usual.

Adding tests with large files

If a test file is larger than 1 MiB, then put it in the resolwe_bio/tests/files/large/ directory. Git Large File Storage (LFS) extension will automatically pick it up and treat it appropriately.

To ensure contributors without Git LFS or users using the source distribution can smoothly run the tests, decorate the tests using large files with the following:

@skipUnlessLargeFiles(<large-file1>, <large-file2>, ...)

where <large-file1>, <large-file2>, … represent the names of large files used inside a particular test.

The decorator will ensure the test is skipped unless these files are present and represent real large files (not just Git LFS pointers).

Building documentation

python setup.py build_sphinx

Note

To build the documentation, you must use Python 3 (Python 2 is not supported).

Preparing release

Follow Resolwe’s documentation on preparing a release. Resolwe code is automatically released to PyPI when tagged, but this is not supported in Resolwe Bioinformatics yet. After you have completed the first part, follow the steps below to release the code on PyPI.

Clean build directory:

python setup.py clean -a

Remove previous distributions in dist directory:

rm dist/*

Remove previous egg-info directory:

rm -r *.egg-info

Create source distribution:

python setup.py sdist

Build wheel:

python setup.py bdist_wheel

Upload distribution to PyPI:

twine upload dist/*

Indices and tables