Explore Workflows

View already parsed workflows here or click here to add your own

Graph	Name	Retrieved From	View
	sum-wf-noET.cwl	https://github.com/common-workflow-language/cwl-v1.1.git Path: tests/sum-wf-noET.cwl Branch/Commit ID: e515226f8ac0f7985cd94dae4a301150adae3050
	Unaligned BAM to BQSR and VCF	https://github.com/genome/analysis-workflows.git Path: definitions/subworkflows/bam_to_bqsr.cwl Branch/Commit ID: a3e26136043c03192c38c335316d2d36e3e67478
	scatter-valuefrom-wf4.cwl#main	https://github.com/common-workflow-language/cwltool.git Path: cwltool/schemas/v1.0/v1.0/scatter-valuefrom-wf4.cwl Branch/Commit ID: 7dec97bb8f0bc2d9e9eb710faf41f2e98cc7cdda Packed ID: main
	gathered exome alignment and somatic variant detection for cle purpose	https://github.com/genome/analysis-workflows.git Path: definitions/pipelines/somatic_exome_cle_gathered.cwl Branch/Commit ID: 25eab0390f6866ce491b44c89d9e0435d228ab6f
	Chipseq alignment for nonhuman with qc and creating homer tag directory	https://github.com/genome/analysis-workflows.git Path: definitions/pipelines/chipseq_alignment_nonhuman.cwl Branch/Commit ID: 25eab0390f6866ce491b44c89d9e0435d228ab6f
	running cellranger mkfastq and count	https://github.com/genome/analysis-workflows.git Path: definitions/subworkflows/cellranger_mkfastq_and_count.cwl Branch/Commit ID: b7d9ace34664d3cedb16f2512c8a6dc6debfc8ca
	workflow-fetch-phobius.cwl	https://github.com/ebi-wp/webservice-cwl.git Path: workflows/workflow-fetch-phobius.cwl Branch/Commit ID: 7c2c01c23d7a68a4f0c608881280576d65a01325
	no-inputs-wf.cwl Workflow without inputs.	https://github.com/common-workflow-language/cwl-v1.1.git Path: tests/no-inputs-wf.cwl Branch/Commit ID: 664835e83eb5e57eee18a04ce7b05fb9d70d77b7
	wf-loadContents.cwl	https://github.com/common-workflow-language/cwl-v1.2.git Path: tests/wf-loadContents.cwl Branch/Commit ID: 5f27e234b4ca88ed1280dedf9e3391a01de12912
	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	https://github.com/datirium/workflows.git Path: workflows/gseapy.cwl Branch/Commit ID: ebbf23764ede324cabc064bd50647c1f643726fa