Explore Workflows

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

Graph Name Retrieved From View
workflow graph genome-kallisto-index.cwl

Generates a FASTA file with the DNA sequences for all transcripts in a GFF file and builds kallisto index

https://github.com/Barski-lab/workflows.git

Path: tools/genome-kallisto-index.cwl

Branch/Commit ID: 144eee15187c1a1145ce1ee0239da69059fd2752
workflow graph trim-rnaseq-pe.cwl

Runs RNA-Seq BioWardrobe basic analysis with pair-end data file.

https://github.com/Barski-lab/workflows.git

Path: workflows/trim-rnaseq-pe.cwl

Branch/Commit ID: 144eee15187c1a1145ce1ee0239da69059fd2752
workflow graph Execute CRISPR

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

Path: bacterial_mobile_elem/wf_bacterial_mobile_elem.cwl

Branch/Commit ID: 54c5074587af001a44eccb4762a4cb25fa24cb3e
workflow graph hello-workflow.cwl

https://github.com/inab/hello-workflows.git

Path: cwl/hello-workflow.cwl

Branch/Commit ID: 8244ac023978e7e3b63f1d3e1fff47b34ce57795
workflow graph wf-loadContents2.cwl

https://github.com/common-workflow-language/cwl-v1.2.git

Path: tests/wf-loadContents2.cwl

Branch/Commit ID: e62f99dd79d6cb9c157cceb458f74200da84f6e9
workflow graph Pipeline for evaluating differential expression of genes across datasets

https://github.com/hubmapconsortium/rna-data-products.git

Path: pipeline.cwl

Branch/Commit ID: 3ac99bca8bfc5686823b65cb95b7ae487f567d3c
workflow graph cnv_exomedepth

CNV ExomeDepth calling

https://gitlab.bsc.es/lrodrig1/structuralvariants_poc.git

Path: structuralvariants/cwl/subworkflows/cnv_exome_depth.cwl

Branch/Commit ID: 3f6a871f81f343cf81a345f73ff2eeac70804b8c
workflow graph Cell Ranger Build Reference Indices

Devel version of Cell Ranger Build Reference Indices pipeline =============================================================

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

Path: workflows/cellranger-mkref.cwl

Branch/Commit ID: 7ced5a5259dbd8b3fc64456beaeffd44f4a24081
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: d6f58c383d0676269afb519399061191a1144a6a
workflow graph tt_blastn_wnode

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

Path: task_types/tt_blastn_wnode.cwl

Branch/Commit ID: e0fb04a0d8bc648183c6b71d099ce7aea3c3b3ff