Explore Workflows

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

Path: vecscreen/bacterial_screening.cwl

Branch/Commit ID: 505b91e41741ccbcd5ebd2b6a09a3be604f9ece3

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

Path: definitions/subworkflows/docm_cle.cwl

Branch/Commit ID: a59a803e1809a8fbfabca6b8962a8ad66dd01f1d

GSEAPY: Gene Set Enrichment Analysis in Python ============================================== Gene Set Enrichment Analysis is a computational method that determines whether an a priori defined set of genes shows statistically significant, concordant differences between two biological states (e.g. phenotypes). GSEA requires as input an expression dataset, which contains expression profiles for multiple samples. While the software supports multiple input file formats for these datasets, the tab-delimited GCT format is the most common. The first column of the GCT file contains feature identifiers (gene ids or symbols in the case of data derived from RNA-Seq experiments). The second column contains a description of the feature; this column is ignored by GSEA and may be filled with “NA”s. Subsequent columns contain the expression values for each feature, with one sample's expression value per column. It is important to note that there are no hard and fast rules regarding how a GCT file's expression values are derived. The important point is that they are comparable to one another across features within a sample and comparable to one another across samples. Tools such as DESeq2 can be made to produce properly normalized data (normalized counts) which are compatible with GSEA.

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

Path: workflows/gseapy.cwl

Branch/Commit ID: 4a5c59829ff8b9f3c843e66e3c675dcd9c689ed5

Workflow runs [Bowtie](http://bowtie-bio.sourceforge.net/tutorial.shtml) v1.2.0 (12/30/2016) to build indices for reference genome provided in a single FASTA file as fasta_file input. Generated indices are saved in a folder with the name that corresponds to the input genome

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

Path: workflows/bowtie-index.cwl

Branch/Commit ID: 9e3c3e65c19873cd1ed3cf7cc3b94ebc75ae0cc5

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

Path: definitions/subworkflows/cram_to_cnvkit.cwl

Branch/Commit ID: 479c9b3e3fa32ec9c7cd4073cfbccc675fd254d9

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

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

Branch/Commit ID: d3ae7483f860339a12c5f404de9db0f026571f77

This workflow creates tagAlign file

https://github.com/ncbi/cwl-ngs-workflows-cbb.git

Path: workflows/File-formats/create-tagAlign.cwl

Branch/Commit ID: 11f70a71cb68b3960c2d410ba1fdcd3b8a7e1419

Workflow runs homer-make-tag-directory.cwl tool using scatter for the following inputs - bam_file - fragment_size - total_reads `dotproduct` is used as a `scatterMethod`, so one element will be taken from each array to construct each job: 1) bam_file[0] fragment_size[0] total_reads[0] 2) bam_file[1] fragment_size[1] total_reads[1] ... N) bam_file[N] fragment_size[N] total_reads[N] `bam_file`, `fragment_size` and `total_reads` arrays should have the identical order.

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

Path: tools/heatmap-prepare.cwl

Branch/Commit ID: 5c0d21fe4f180730d4f6dd301e785bd6b00d5907

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

Path: protein_alignment/wf_seed_1.cwl

Branch/Commit ID: 505b91e41741ccbcd5ebd2b6a09a3be604f9ece3

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

Path: definitions/subworkflows/mutect.cwl

Branch/Commit ID: 889a077a20c0fdb01f4ed97aa4bc40f920c37a1a