Explore Workflows

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

Graph Name Retrieved From View
workflow graph process VCF workflow

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

Path: definitions/subworkflows/strelka_process_vcf.cwl

Branch/Commit ID: 0c4f4e59c265eb22aed3d2d37b173cb5430773d2
workflow graph Execute CRISPR

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

Path: bacterial_mobile_elem/wf_bacterial_mobile_elem.cwl

Branch/Commit ID: cb15f907132fb90bc66b39bb0af3c211801feba1
workflow graph tt_fscr_calls_pass1

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

Path: task_types/tt_fscr_calls_pass1.cwl

Branch/Commit ID: e668f9c4047f1971ae53040a5af3eccc4bfc3c53
workflow graph Add snv and indel bam-readcount files to a vcf

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

Path: definitions/subworkflows/vcf_readcount_annotator.cwl

Branch/Commit ID: 258bd4353ad1ca7790b3ae626bf42ab8194e7561
workflow graph count-lines11-wf.cwl

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

Path: cwltool/schemas/v1.0/v1.0/count-lines11-wf.cwl

Branch/Commit ID: 1eb6bfe3c77aebaf69453a669d21ae7a5a78056f
workflow graph scatter-valuefrom-wf2.cwl

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

Path: cwltool/schemas/v1.0/v1.0/scatter-valuefrom-wf2.cwl

Branch/Commit ID: 1eb6bfe3c77aebaf69453a669d21ae7a5a78056f
workflow graph Single-cell Differential Expression

Single-cell Differential Expression =================================== Runs differential expression analysis for a subset of cells between two selected conditions.

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

Path: workflows/sc_diff_expr.cwl

Branch/Commit ID: 36fd18f11e939d3908b1eca8d2939402f7a99b0f
workflow graph checkm

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

Path: checkm/wf_checkm.cwl

Branch/Commit ID: cb15f907132fb90bc66b39bb0af3c211801feba1
workflow graph Per-region pindel

https://github.com/apaul7/cancer-genomics-workflow.git

Path: definitions/subworkflows/pindel_cat.cwl

Branch/Commit ID: bfcb5ffbea3d00a38cc03595d41e53ea976d599d
workflow graph PCA - Principal Component Analysis

Principal Component Analysis --------------- Principal component analysis (PCA) is a statistical procedure that uses an orthogonal transformation to convert a set of observations of possibly correlated variables (entities each of which takes on various numerical values) into a set of values of linearly uncorrelated variables called principal components. The calculation is done by a singular value decomposition of the (centered and possibly scaled) data matrix, not by using eigen on the covariance matrix. This is generally the preferred method for numerical accuracy.

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

Path: workflows/pca.cwl

Branch/Commit ID: 22880e0f41d0420a17d643e8a6e8ee18165bbfbf