Explore Workflows

https://github.com/common-workflow-language/cwl-utils.git

Path: testdata/step_valuefrom5_wf_v1_2.cwl

Branch/Commit ID: 124a08ce3389eb49066c34a4163cbbed210a0355

Differential Binding Analysis of ChIP-Seq Peak Data --------------------------------------------------- DiffBind processes ChIP-Seq data enriched for genomic loci where specific protein/DNA binding occurs, including peak sets identified by ChIP-Seq peak callers and aligned sequence read datasets. It is designed to work with multiple peak sets simultaneously, representing different ChIP experiments (antibodies, transcription factor and/or histone marks, experimental conditions, replicates) as well as managing the results of multiple peak callers. For more information please refer to: ------------------------------------- Ross-Innes CS, Stark R, Teschendorff AE, Holmes KA, Ali HR, Dunning MJ, Brown GD, Gojis O, Ellis IO, Green AR, Ali S, Chin S, Palmieri C, Caldas C, Carroll JS (2012). “Differential oestrogen receptor binding is associated with clinical outcome in breast cancer.” Nature, 481, -4.

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

Path: workflows/diffbind.cwl

Branch/Commit ID: 2cad55523d1b4ee7fd9e64df0f6263c6545e4b0e

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

Path: definitions/subworkflows/strelka_and_post_processing.cwl

Branch/Commit ID: 9c0b1497c467393e1a54735575043dced73e95c4

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

Path: v1.0/v1.0/pass-unconnected.cwl

Branch/Commit ID: 17695244222b0301b37cb749fe4a8d89622cd1ad

https://github.com/apaul7/cancer-genomics-workflow.git

Path: definitions/subworkflows/vcf_eval_cle_gold.cwl

Branch/Commit ID: bfcb5ffbea3d00a38cc03595d41e53ea976d599d

Note: should be updated The original [BioWardrobe's](https://biowardrobe.com) [PubMed ID:26248465](https://www.ncbi.nlm.nih.gov/pubmed/26248465) **RNA-Seq** basic analysis for a **single-end** experiment. A corresponded input [FASTQ](http://maq.sourceforge.net/fastq.shtml) file has to be provided. Current workflow should be used only with the single-end RNA-Seq data. It performs the following steps: 1. Trim adapters from input FASTQ file 2. Use STAR to align reads from input FASTQ file according to the predefined reference indices; generate unsorted BAM file and alignment statistics file 3. Use fastx_quality_stats to analyze input FASTQ file and generate quality statistics file 4. Use samtools sort to generate coordinate sorted BAM(+BAI) file pair from the unsorted BAM file obtained on the step 1 (after running STAR) 5. Generate BigWig file on the base of sorted BAM file 6. Map input FASTQ file to predefined rRNA reference indices using Bowtie to define the level of rRNA contamination; export resulted statistics to file 7. Calculate isoform expression level for the sorted BAM file and GTF/TAB annotation file using GEEP reads-counting utility; export results to file

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

Path: workflows/trim-rnaseq-se-dutp.cwl

Branch/Commit ID: a68821bf3a9ceadc3b2ffbb535d601d9a645b377

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

Path: definitions/subworkflows/varscan_germline.cwl

Branch/Commit ID: 51724b44c96e5fd849ae55b752865b80bc47d66c

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

Path: definitions/pipelines/germline_exome_hla_typing.cwl

Branch/Commit ID: 00df82a529a58d362158110581e1daa28b4d7ecb

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

Path: cwltool/schemas/v1.0/v1.0/count-lines3-wf.cwl

Branch/Commit ID: 203797516329f7fb8aa5e763e6f9b331c63c3060

https://github.com/PMCC-BioinformaticsCore/janis-pipelines.git

Path: janis_pipelines/wgs_somatic/cwl/tools/vardictSomaticVariantCaller_v0_1_0.cwl

Branch/Commit ID: 3fd91f30b041f222e0dc3d5bb5544cc6de38d3c3