Explore Workflows

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

Path: task_types/tt_ani_top_n.cwl

Branch/Commit ID: 68058b108cb5b0b72ebe244c42eefa2747e1d64a

What is THOR? -------------- THOR is an HMM-based approach to detect and analyze differential peaks in two sets of ChIP-seq data from distinct biological conditions with replicates. THOR performs genomic signal processing, peak calling and p-value calculation in an integrated framework. For more information please refer to: ------------------------------------- Allhoff, M., Sere K., Freitas, J., Zenke, M., Costa, I.G. (2016), Differential Peak Calling of ChIP-seq Signals with Replicates with THOR, Nucleic Acids Research, epub gkw680.

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

Path: workflows/rgt-thor.cwl

Branch/Commit ID: 93b844a80f4008cc973ea9b5efedaff32a343895

Differential Binding Analysis of ChIP-Seq or CUT&RUN/Tag Peak Data --------------------------------------------------- DiffBind processes ChIP-Seq or CUT&RUN/Tag data enriched for genomic loci where specific protein/DNA binding occurs, including peak sets identified by peak caller tools and aligned sequence read datasets. It is designed to work with multiple peak sets simultaneously, representing different ChIP or CUT&RUN/Tag 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: 93b844a80f4008cc973ea9b5efedaff32a343895

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

Path: definitions/subworkflows/hs_metrics.cwl

Branch/Commit ID: 31602b94b34ff55876147c7299e1bec47e8d1a31

Single-cell WNN Cluster Analysis Clusters multiome ATAC and RNA-Seq datasets, identifies gene markers and differentially accessible peaks.

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

Path: workflows/sc-wnn-cluster.cwl

Branch/Commit ID: 36fd18f11e939d3908b1eca8d2939402f7a99b0f

Runs RNA-Seq BioWardrobe basic analysis with strand specific pair-end data file.

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

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

Branch/Commit ID: e284e3f6dff25037b209895c52f2abd37a1ce1bf

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

Path: tests/wf/mut2.cwl

Branch/Commit ID: 4df56e95e6fceab69e677b539f3532cbf5946197

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

Path: cwltool/schemas/v1.0/v1.0/count-lines10-wf.cwl

Branch/Commit ID: 6e9f82a6d2195d4f16f28fd6e1485138372fb430

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

Path: task_types/tt_bact_get_kmer_reference.cwl

Branch/Commit ID: 3a89a217ca75ec042ce3a11ebb6d1664a3ec6e7e

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: f3e44d3b0f198cf5245c49011124dc3b6c2b06fd