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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: 69643d8c15f5357a320aa7e2f6adb2e71302fd20
workflow graph binning.cwl

https://github.com/EBI-Metagenomics/CWL-binning.git

Path: workflows/binning.cwl

Branch/Commit ID: 895abf7343a1039e5fd7a509af082425009be2dd
workflow graph chksum_xam_to_interleaved_fq.cwl

https://github.com/cancerit/workflow-seq-import.git

Path: cwls/chksum_xam_to_interleaved_fq.cwl

Branch/Commit ID: 2e592d7253c814aae74e12934211d01da21e957e
workflow graph rna amplicon analysis for fasta files

RNAs - qc, preprocess, annotation, index, abundance

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

Path: CWL/Workflows/amplicon-fasta.workflow.cwl

Branch/Commit ID: f906212e2c9a88280ae36545e5422f25752aa8f4
workflow graph conflict-wf.cwl#collision

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

Path: cwltool/schemas/v1.0/v1.0/conflict-wf.cwl

Branch/Commit ID: bfe56f3138e9e6fc0b9b8c06447553d4cea03d59

Packed ID: collision
workflow graph bam to trimmed fastqs and biscuit alignments

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

Path: definitions/subworkflows/bam_to_trimmed_fastq_and_biscuit_alignments.cwl

Branch/Commit ID: a3e26136043c03192c38c335316d2d36e3e67478
workflow graph tt_kmer_top_n.cwl

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

Path: task_types/tt_kmer_top_n.cwl

Branch/Commit ID: c64599f5db2437f9323d41cc3d8d9efb20a2667e
workflow graph kmer_build_tree

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

Path: task_types/tt_kmer_build_tree.cwl

Branch/Commit ID: c64599f5db2437f9323d41cc3d8d9efb20a2667e
workflow graph umi duplex alignment fastq workflow

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

Path: definitions/pipelines/alignment_umi_duplex.cwl

Branch/Commit ID: 3034168d652bfa930ba09af20e473a4564a8010d
workflow graph assm_assm_blastn_wnode

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

Path: task_types/tt_assm_assm_blastn_wnode.cwl

Branch/Commit ID: c64599f5db2437f9323d41cc3d8d9efb20a2667e