Explore Workflows

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

Path: cwltool/schemas/v1.0/v1.0/js-expr-req-wf.cwl

Branch/Commit ID: 89ccbfc53ff3bb6abe2eb90bb7e0091c54c18f5c

Packed ID: wf

CNV CODEX calling

https://gitlab.bsc.es/lrodrig1/structuralvariants_poc.git

Path: structuralvariants/cwl/abstract_operations/subworkflows/cnv_codex.cwl

Branch/Commit ID: de9cb009f8fe0c8d5a94db5c882cf21ddf372452

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

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

Branch/Commit ID: cf9d7cdefa6dfb3b678636da02bc55b6108c04ac

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

Path: cwltool/schemas/v1.0/v1.0/steplevel-resreq.cwl

Branch/Commit ID: 227f35a5ed50c423afba2353871950aa61d58872

Workflow to build different indices for different tools from a genome and transcriptome. This workflow expects an (annotated) genome in GBOL ttl format. Steps: - SAPP: rdf2gtf (genome fasta) - SAPP: rdf2fasta (transcripts fasta) - STAR index (Optional for Eukaryotic origin) - bowtie2 index - kallisto index

https://git.wur.nl/unlock/cwl.git

Path: cwl/workflows/workflow_indexbuilder.cwl

Branch/Commit ID: b9097b82e6ab6f2c9496013ce4dd6877092956a0

What is MAnorm? -------------- MAnorm is a robust model for quantitative comparison of ChIP-Seq data sets of TFs (transcription factors) or epigenetic modifications and you can use it for: * Normalization of two ChIP-seq samples * Quantitative comparison (differential analysis) of two ChIP-seq samples * Evaluating the overlap enrichment of the protein binding sites(peaks) * Elucidating underlying mechanisms of cell-type specific gene regulation How MAnorm works? ---------------- MAnorm uses common peaks of two samples as a reference to build the rescaling model for normalization, which is based on the empirical assumption that if a chromatin-associated protein has a substantial number of peaks shared in two conditions, the binding at these common regions will tend to be determined by similar mechanisms, and thus should exhibit similar global binding intensities across samples. The observed differences on common peaks are presumed to reflect the scaling relationship of ChIP-Seq signals between two samples, which can be applied to all peaks. What do the inputs mean? ---------------- ### General **Experiment short name/Alias** * short name for you experiment to identify among the others **ChIP-Seq PE sample 1** * previously analyzed ChIP-Seq paired-end experiment to be used as Sample 1 **ChIP-Seq PE sample 2** * previously analyzed ChIP-Seq paired-end experiment to be used as Sample 2 **Genome** * Reference genome to be used for gene assigning ### Advanced **Reads shift size for sample 1** * This value is used to shift reads towards 3' direction to determine the precise binding site. Set as half of the fragment length. Default 100 **Reads shift size for sample 2** * This value is used to shift reads towards 5' direction to determine the precise binding site. Set as half of the fragment length. Default 100 **M-value (log2-ratio) cutoff** * Absolute M-value (log2-ratio) cutoff to define biased (differential binding) peaks. Default: 1.0 **P-value cutoff** * P-value cutoff to define biased peaks. Default: 0.01 **Window size** * Window size to count reads and calculate read densities. 2000 is recommended for sharp histone marks like H3K4me3 and H3K27ac, and 1000 for TFs or DNase-seq. Default: 2000

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

Path: workflows/manorm-pe.cwl

Branch/Commit ID: 2005c6b7f1bff6247d015ff6c116bd9ec97158bb

https://github.com/mskcc/ACCESS-Pipeline.git

Path: workflows/BQSR/bqsr_workflow.cwl

Branch/Commit ID: 09ddd9711fb550f56d52f1806cdefd4a8cd943b0

https://github.com/arvados/bh20-seq-resource.git

Path: workflows/pangenome-generate/pangenome-generate.cwl

Branch/Commit ID: ae4cb3c2cf7103bbc84f52618bb755d7ce25775b

Creates indices for: * [STAR](https://github.com/alexdobin/STAR) v2.5.3a (03/17/2017) PMID: [23104886](https://www.ncbi.nlm.nih.gov/pubmed/23104886) * [bowtie](http://bowtie-bio.sourceforge.net/tutorial.shtml) v1.2.0 (12/30/2016) It performs the following steps: 1. `STAR --runMode genomeGenerate` to generate indices, based on [FASTA](http://zhanglab.ccmb.med.umich.edu/FASTA/) and [GTF](http://mblab.wustl.edu/GTF2.html) input files, returns results as an array of files 2. Outputs indices as [Direcotry](http://www.commonwl.org/v1.0/CommandLineTool.html#Directory) data type 3. Separates *chrNameLength.txt* file from Directory output 4. `bowtie-build` to generate indices requires genome [FASTA](http://zhanglab.ccmb.med.umich.edu/FASTA/) file as input, returns results as a group of main and secondary files

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

Path: workflows/genome-indices.cwl

Branch/Commit ID: 2005c6b7f1bff6247d015ff6c116bd9ec97158bb

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

Path: workflows/copy_outputs.cwl

Branch/Commit ID: 4034144f39a9428307e82efe1f812c1d37c79de5