Explore Workflows

1. Convert input SRA file into pair of upsrtream and downstream FASTQ files (run fastq-dump) 2. Analyze quality of FASTQ files (run fastqc with each of the FASTQ files) 3. If any of the following fields in fastqc generated report is marked as failed for at least one of input FASTQ files: \"Per base sequence quality\", \"Per sequence quality scores\", \"Overrepresented sequences\", \"Adapter Content\", - trim adapters (run trimmomatic) 4. Align original or trimmed FASTQ files to reference genome, calculate genes and isoforms expression (run RSEM) 5. Count mapped reads number in sorted BAM file (run bamtools stats) 6. Generate genome coverage BED file (run bedtools genomecov) 7. Sort genearted BED file (run sort) 8. Generate genome coverage bigWig file from BED file (run bedGraphToBigWig)

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

Path: workflows/xenbase-rnaseq-se.cwl

Branch/Commit ID: dda9e6e06a656b7b3fa7504156474b962fe3953c

https://github.com/ncbi/pgap.git

Path: bacterial_noncoding/wf_gcmsearch.cwl

Branch/Commit ID: cb15f907132fb90bc66b39bb0af3c211801feba1

Simulation steps pipeline

https://github.com/ILIAD-ocean-twin/application_package.git

Path: workflow_in_workflow/workflow_same_level_v2.cwl

Branch/Commit ID: 9a0db98839bbc655e12d49f56c61deecd77ff14c

Packed ID: main_pipeline

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

Path: tests/wf/mut3.cwl

Branch/Commit ID: bffea7fd5e864c5221c13a815d00d0a2fad178cc

https://github.com/ncbi/pgap.git

Path: task_types/tt_kmer_ref_compare_wnode.cwl

Branch/Commit ID: b4a6e46405c08e0b14ad92f0ab38bcc4a69caa5c

https://github.com/genome/analysis-workflows.git

Path: definitions/subworkflows/pindel_cat.cwl

Branch/Commit ID: 0c4f4e59c265eb22aed3d2d37b173cb5430773d2

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: ee66d03be8a7fd61367db40c37a973ff55ece4da

# Set Operations for Peaks This workflow takes as input multiple peak list TSV files (the `iaintersect_result.tsv` output under the \"Files\" output tab) from the ChIP, ATAC, C&R, or diffbind workflows and performs the user-selected set operation on the group. Set operations include intersection, union, difference, and complement. See the tooltip for the `set_operator` input for more details.

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

Path: workflows/filter-peaks-by-overlap.cwl

Branch/Commit ID: 57863b6131d8262c5ce864adaf8e4038401e71a2

https://github.com/mskcc/pluto-cwl.git

Path: cwl/concat.cwl

Branch/Commit ID: 462f6015c9268a4205b6e81de018a470b8a4a153

https://github.com/ncbi/pgap.git

Path: protein_alignment/wf_compart_filter_prosplign.cwl

Branch/Commit ID: cb15f907132fb90bc66b39bb0af3c211801feba1