Explore Workflows

Workflow runs group-isoforms.cwl tool using scatter for isoforms_file input. genes_filename and common_tss_filename inputs are ignored.

https://github.com/datirium/workflows.git

Path: tools/group-isoforms-batch.cwl

Branch/Commit ID: 7fb8a1ebf8145791440bc2fed9c5f2d78a19d04c

Copy fasta_file file to the folder and run run bismark_genome_preparation script to prepare indices for Bismark Methylation Analysis. Bowtie2 aligner is used by default. The name of the output indices folder is equal to the genome input.

https://github.com/datirium/workflows.git

Path: workflows/bismark-index.cwl

Branch/Commit ID: 2cad55523d1b4ee7fd9e64df0f6263c6545e4b0e

https://github.com/Barski-lab/workflows.git

Path: subworkflows/xenbase-sra-to-fastq-pe.cwl

Branch/Commit ID: 877546bb89b793cc8830f8d803858706937a654b

Cellranger Reanalyze ====================

https://github.com/datirium/workflows.git

Path: workflows/cellranger-reanalyze.cwl

Branch/Commit ID: 10ce6e113f749c7bd725e426445220c3bdc5ddf1

https://github.com/datirium/workflows.git

Path: subworkflows/allele-process-strain.cwl

Branch/Commit ID: ae2b231562822ed66b8e35e5452ae7f012416b2a

The original [BioWardrobe's](https://biowardrobe.com) [PubMed ID:26248465](https://www.ncbi.nlm.nih.gov/pubmed/26248465) **ChIP-Seq** basic analysis workflow for a **paired-end** experiment with Trim Galore. _Trim Galore_ is a wrapper around [Cutadapt](https://github.com/marcelm/cutadapt) and [FastQC](http://www.bioinformatics.babraham.ac.uk/projects/fastqc/) to consistently apply adapter and quality trimming to FastQ files, with extra functionality for RRBS data. A [FASTQ](http://maq.sourceforge.net/fastq.shtml) input file has to be provided. In outputs it returns coordinate sorted BAM file alongside with index BAI file, quality statistics for both the input FASTQ files, reads coverage in a form of BigWig file, peaks calling data in a form of narrowPeak or broadPeak files, islands with the assigned nearest genes and region type, data for average tag density plot (on the base of BAM file). Workflow starts with running fastx_quality_stats (steps fastx_quality_stats_upstream and fastx_quality_stats_downstream) from FASTX-Toolkit to calculate quality statistics for both upstream and downstream input FASTQ files. At the same time Bowtie is used to align reads from input FASTQ files to reference genome (Step bowtie_aligner). The output of this step is unsorted SAM file which is being sorted and indexed by samtools sort and samtools index (Step samtools_sort_index). Depending on workflow’s input parameters indexed and sorted BAM file could be processed by samtools rmdup (Step samtools_rmdup) to remove all possible read duplicates. In a case when removing duplicates is not necessary the step returns original input BAM and BAI files without any processing. If the duplicates were removed the following step (Step samtools_sort_index_after_rmdup) reruns samtools sort and samtools index with BAM and BAI files, if not - the step returns original unchanged input files. Right after that macs2 callpeak performs peak calling (Step macs2_callpeak). On the base of returned outputs the next step (Step macs2_island_count) calculates the number of islands and estimated fragment size. If the last one is less that 80 (hardcoded in a workflow) macs2 callpeak is rerun again with forced fixed fragment size value (Step macs2_callpeak_forced). If at the very beginning it was set in workflow input parameters to force run peak calling with fixed fragment size, this step is skipped and the original peak calling results are saved. In the next step workflow again calculates the number of islands and estimated fragment size (Step macs2_island_count_forced) for the data obtained from macs2_callpeak_forced step. If the last one was skipped the results from macs2_island_count_forced step are equal to the ones obtained from macs2_island_count step. Next step (Step macs2_stat) is used to define which of the islands and estimated fragment size should be used in workflow output: either from macs2_island_count step or from macs2_island_count_forced step. If input trigger of this step is set to True it means that macs2_callpeak_forced step was run and it returned different from macs2_callpeak step results, so macs2_stat step should return [fragments_new, fragments_old, islands_new], if trigger is False the step returns [fragments_old, fragments_old, islands_old], where sufix \"old\" defines results obtained from macs2_island_count step and sufix \"new\" - from macs2_island_count_forced step. The following two steps (Step bamtools_stats and bam_to_bigwig) are used to calculate coverage on the base of input BAM file and save it in BigWig format. For that purpose bamtools stats returns the number of mapped reads number which is then used as scaling factor by bedtools genomecov when it performs coverage calculation and saves it in BED format. The last one is then being sorted and converted to BigWig format by bedGraphToBigWig tool from UCSC utilities. Step get_stat is used to return a text file with statistics in a form of [TOTAL, ALIGNED, SUPRESSED, USED] reads count. Step island_intersect assigns genes and regions to the islands obtained from macs2_callpeak_forced. Step average_tag_density is used to calculate data for average tag density plot on the base of BAM file.

https://github.com/datirium/workflows.git

Path: workflows/trim-chipseq-pe.cwl

Branch/Commit ID: c602e3cdd72ff904dd54d46ba2b5146eb1c57022

https://github.com/yeolab/eclip.git

Path: cwl/wf_clipseqcore_chimeric_se_1barcode.cwl

Branch/Commit ID: 49a9bcda10de8f55fab2481f424eb9cdf2e5b256

Sequence reads are first cleaned from adapters and transformed into fully bisulfite-converted forward (C->T) and reverse read (G->A conversion of the forward strand) versions, before they are aligned to similarly converted versions of the genome (also C->T and G->A converted). Sequence reads that produce a unique best alignment from the four alignment processes against the bisulfite genomes (which are running in parallel) are then compared to the normal genomic sequence and the methylation state of all cytosine positions in the read is inferred. A read is considered to align uniquely if an alignment has a unique best alignment score (as reported by the AS:i field). If a read produces several alignments with the same number of mismatches or with the same alignment score (AS:i field), a read (or a read-pair) is discarded altogether. On the next step we extract the methylation call for every single C analysed. The position of every single C will be written out to a new output file, depending on its context (CpG, CHG or CHH), whereby methylated Cs will be labelled as forward reads (+), non-methylated Cs as reverse reads (-). The output of the methylation extractor is then transformed into a bedGraph and coverage file. The bedGraph counts output is then used to generate a genome-wide cytosine report which reports the number on every single CpG (optionally every single cytosine) in the genome, irrespective of whether it was covered by any reads or not. As this type of report is informative for cytosines on both strands the output may be fairly large (~46mn CpG positions or >1.2bn total cytosine positions in the human genome).

https://github.com/datirium/workflows.git

Path: workflows/bismark-methylation-se.cwl

Branch/Commit ID: 2cad55523d1b4ee7fd9e64df0f6263c6545e4b0e

https://github.com/common-workflow-language/cwltool.git

Path: tests/wf/scatter2.cwl

Branch/Commit ID: 1441c285e8a5afe399f5d52ca9059cb8bb513edb

The original [BioWardrobe's](https://biowardrobe.com) [PubMed ID:26248465](https://www.ncbi.nlm.nih.gov/pubmed/26248465) **ChIP-Seq** basic analysis workflow for a **paired-end** experiment with Trim Galore. _Trim Galore_ is a wrapper around [Cutadapt](https://github.com/marcelm/cutadapt) and [FastQC](http://www.bioinformatics.babraham.ac.uk/projects/fastqc/) to consistently apply adapter and quality trimming to FastQ files, with extra functionality for RRBS data. A [FASTQ](http://maq.sourceforge.net/fastq.shtml) input file has to be provided. In outputs it returns coordinate sorted BAM file alongside with index BAI file, quality statistics for both the input FASTQ files, reads coverage in a form of BigWig file, peaks calling data in a form of narrowPeak or broadPeak files, islands with the assigned nearest genes and region type, data for average tag density plot (on the base of BAM file). Workflow starts with running fastx_quality_stats (steps fastx_quality_stats_upstream and fastx_quality_stats_downstream) from FASTX-Toolkit to calculate quality statistics for both upstream and downstream input FASTQ files. At the same time Bowtie is used to align reads from input FASTQ files to reference genome (Step bowtie_aligner). The output of this step is unsorted SAM file which is being sorted and indexed by samtools sort and samtools index (Step samtools_sort_index). Depending on workflow’s input parameters indexed and sorted BAM file could be processed by samtools rmdup (Step samtools_rmdup) to remove all possible read duplicates. In a case when removing duplicates is not necessary the step returns original input BAM and BAI files without any processing. If the duplicates were removed the following step (Step samtools_sort_index_after_rmdup) reruns samtools sort and samtools index with BAM and BAI files, if not - the step returns original unchanged input files. Right after that macs2 callpeak performs peak calling (Step macs2_callpeak). On the base of returned outputs the next step (Step macs2_island_count) calculates the number of islands and estimated fragment size. If the last one is less that 80 (hardcoded in a workflow) macs2 callpeak is rerun again with forced fixed fragment size value (Step macs2_callpeak_forced). If at the very beginning it was set in workflow input parameters to force run peak calling with fixed fragment size, this step is skipped and the original peak calling results are saved. In the next step workflow again calculates the number of islands and estimated fragment size (Step macs2_island_count_forced) for the data obtained from macs2_callpeak_forced step. If the last one was skipped the results from macs2_island_count_forced step are equal to the ones obtained from macs2_island_count step. Next step (Step macs2_stat) is used to define which of the islands and estimated fragment size should be used in workflow output: either from macs2_island_count step or from macs2_island_count_forced step. If input trigger of this step is set to True it means that macs2_callpeak_forced step was run and it returned different from macs2_callpeak step results, so macs2_stat step should return [fragments_new, fragments_old, islands_new], if trigger is False the step returns [fragments_old, fragments_old, islands_old], where sufix \"old\" defines results obtained from macs2_island_count step and sufix \"new\" - from macs2_island_count_forced step. The following two steps (Step bamtools_stats and bam_to_bigwig) are used to calculate coverage on the base of input BAM file and save it in BigWig format. For that purpose bamtools stats returns the number of mapped reads number which is then used as scaling factor by bedtools genomecov when it performs coverage calculation and saves it in BED format. The last one is then being sorted and converted to BigWig format by bedGraphToBigWig tool from UCSC utilities. Step get_stat is used to return a text file with statistics in a form of [TOTAL, ALIGNED, SUPRESSED, USED] reads count. Step island_intersect assigns genes and regions to the islands obtained from macs2_callpeak_forced. Step average_tag_density is used to calculate data for average tag density plot on the base of BAM file.

https://github.com/datirium/workflows.git

Path: workflows/trim-chipseq-pe.cwl

Branch/Commit ID: 91bb63948c0a264334b9007ef85f936768d90d11