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Graph Name Retrieved From View
workflow graph GSEApy - Gene Set Enrichment Analysis in Python

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. Documents ============================================== - GSEA Home Page: https://www.gsea-msigdb.org/gsea/index.jsp - Results Interpretation: https://www.gsea-msigdb.org/gsea/doc/GSEAUserGuideTEXT.htm#_Interpreting_GSEA_Results - GSEA User Guide: https://gseapy.readthedocs.io/en/latest/faq.html - GSEAPY Docs: https://gseapy.readthedocs.io/en/latest/introduction.html References ============================================== - Subramanian, Tamayo, et al. (2005, PNAS), https://www.pnas.org/content/102/43/15545 - Mootha, Lindgren, et al. (2003, Nature Genetics), http://www.nature.com/ng/journal/v34/n3/abs/ng1180.html - Chen EY, Tan CM, Kou Y, Duan Q, Wang Z, Meirelles GV, Clark NR, Ma'ayan A. Enrichr: interactive and collaborative HTML5 gene list enrichment analysis tool. BMC Bioinformatics. 2013; 128(14). - Kuleshov MV, Jones MR, Rouillard AD, Fernandez NF, Duan Q, Wang Z, Koplev S, Jenkins SL, Jagodnik KM, Lachmann A, McDermott MG, Monteiro CD, Gundersen GW, Ma'ayan A. Enrichr: a comprehensive gene set enrichment analysis web server 2016 update. Nucleic Acids Research. 2016; gkw377 . - Xie Z, Bailey A, Kuleshov MV, Clarke DJB., Evangelista JE, Jenkins SL, Lachmann A, Wojciechowicz ML, Kropiwnicki E, Jagodnik KM, Jeon M, & Ma’ayan A. Gene set knowledge discovery with Enrichr. Current Protocols, 1, e90. 2021. doi: 10.1002/cpz1.90

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

Path: workflows/gseapy.cwl

Branch/Commit ID: 46d3d403ddb240d5a8f4f31ab992b6d6a2686745
workflow graph blastp_wnode_naming

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

Path: task_types/tt_blastp_wnode_naming.cwl

Branch/Commit ID: 3bec7182e39cb4af10ed8920639adfa78a28ed81
workflow graph Cut-n-Run pipeline paired-end

Experimental pipeline for Cut-n-Run analysis. Uses mapping results from the following experiment types: - `chipseq-pe.cwl` - `trim-chipseq-pe.cwl` - `trim-atacseq-pe.cwl` Note, the upstream analyses should not have duplicates removed

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

Path: workflows/trim-chipseq-pe-cut-n-run.cwl

Branch/Commit ID: 4a80f5b8f86c83af39494ecc309b789aeda77964
workflow graph Perform Molecular Atmospheric Calibration

This workflow performs calibrations, related to the molecular content of the atmosphere. To be updated...

https://gitlab.cta-observatory.org/cta-computing/dpps/dpps-workflows.git

Path: workflows/calibpipe/AtmosphericCalibrations/MolecularAtmosphere/uc-dpps-cp-110.cwl

Branch/Commit ID: eb6a98289850791cd1891c89e5209180c35c7858
workflow graph msi.cwl

https://github.com/mskcc/innovation-pipeline.git

Path: workflows/subworkflows/msi.cwl

Branch/Commit ID: b0f226a9ac5152f3afe0d38c8cd54aa25b8b01cf
workflow graph mut3.cwl

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

Path: tests/wf/mut3.cwl

Branch/Commit ID: a3d565bf8e630101d25d31804cfbceb0a0ba28de
workflow graph fastq_foreign_chromosome_cleanup

This workflow remove foreign chromosome contamination by taxonomic groups

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

Path: workflows/Contamination/fastq-foreign-chromosome-cleanup_test.cwl

Branch/Commit ID: 3247592a89deafaa0d9c5910a1cb1d000ef9b098
workflow graph WGS and MT analysis for fastq files

rna / protein - qc, preprocess, filter, annotation, index, abundance

 https://github.com/MG-RAST/pipeline.git

Path: CWL/Workflows/wgs-fastq.workflow.cwl

Branch/Commit ID: 1844de830f6935901849ccd9966685fbf13e8042
workflow graph rnaseq-pe-dutp-mitochondrial.cwl

RNA-Seq strand specific mitochondrial workflow for pair-end experiment based on original BioWardrobe's basic analysis.

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

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

Branch/Commit ID: 4b8bb1a1ec39056253ca8eee976078e51f4a954e
workflow graph 02-local-compare-across-alg.cwl

https://github.com/PNNL-CompBio/decomprolute.git

Path: localData/02-local-compare-across-alg.cwl

Branch/Commit ID: 6351764c74a44fc4fa2042d31c0cedde5a5bdbe9