Explore Workflows

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

Path: definitions/pipelines/alignment_exome.cwl

Branch/Commit ID: 7638b3075863ae8172f4adaec82fb2eb8e80d3d5

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

Path: metadata/advanced-header.cwl

Branch/Commit ID: 2005c6b7f1bff6247d015ff6c116bd9ec97158bb

https://github.com/pitagora-network/pitagora-cwl.git

Path: workflows/tophat2-cufflinks/paired_end/tophat2-cufflinks_wf_pe.cwl

Branch/Commit ID: f85f2cd5d888ed947f47a391eb32dcb53265f9b3

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

Path: vecscreen/foreign_screening.cwl

Branch/Commit ID: 75ea689c0a8c9902b4598b453455857cb08e885a

ATAC-seq 04 quantification - SE

https://github.com/Duke-GCB/GGR-cwl.git

Path: v1.0/ATAC-seq_pipeline/04-peakcall-se.cwl

Branch/Commit ID: 487af88ef0b971f76ecd1a215639bb47e3ee94e1

https://github.com/pitagora-network/pitagora-cwl.git

Path: workflows/star-stringtie/single_end/star-stringtie_wf_se.cwl

Branch/Commit ID: f85f2cd5d888ed947f47a391eb32dcb53265f9b3

https://github.com/pitagora-network/pitagora-cwl.git

Path: workflows/hisat2-stringtie/single_end/hisat2-stringtie_wf_se.cwl

Branch/Commit ID: f85f2cd5d888ed947f47a391eb32dcb53265f9b3

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: 2005c6b7f1bff6247d015ff6c116bd9ec97158bb

Cell Ranger Aggregate =====================

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

Path: workflows/cellranger-aggr.cwl

Branch/Commit ID: 480e99a4bb3046e0565113d9dca294e0895d3b0c

https://github.com/bcbio/bcbio_validation_workflows.git

Path: somatic-lowfreq/pisces-titr-workflow/wf-variantcall.cwl

Branch/Commit ID: af9a5621efcb44c249697d6df071fe4defe389ac