Explore Workflows

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

Graph Name Retrieved From View
workflow graph cluster_blastp_wnode and gpx_qdump combined

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

Path: task_types/tt_cluster_and_qdump.cwl

Branch/Commit ID: 94c97cfc95a5bf102a6f9206e045ea1afb768317
workflow graph umi molecular alignment workflow

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

Path: definitions/subworkflows/molecular_qc.cwl

Branch/Commit ID: b8000c793d6e7ce4d690406c4f914c5c62acd51f
workflow graph hmmsearch_wnode and gpx_qdump combined workflow to apply scatter/gather

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

Path: task_types/tt_hmmsearch_wnode_plus_qdump.cwl

Branch/Commit ID: 94c97cfc95a5bf102a6f9206e045ea1afb768317
workflow graph Pairwise genomic regions intersection

Pairwise genomic regions intersection ============================================= Overlaps peaks from two ChIP/ATAC experiments

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

Path: workflows/peak-intersect.cwl

Branch/Commit ID: 10ce6e113f749c7bd725e426445220c3bdc5ddf1
workflow graph snaptools_create_snap_file.cwl

https://github.com/hubmapconsortium/sc-atac-seq-pipeline.git

Path: steps/snaptools_create_snap_file.cwl

Branch/Commit ID: 5465f666aac446a6d66fed1819e48a79395f6b02
workflow graph Apply filters to VCF file

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

Path: definitions/subworkflows/germline_filter_vcf.cwl

Branch/Commit ID: b8000c793d6e7ce4d690406c4f914c5c62acd51f
workflow graph Detect Variants workflow for WGS pipeline

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

Path: definitions/pipelines/detect_variants_wgs.cwl

Branch/Commit ID: b8000c793d6e7ce4d690406c4f914c5c62acd51f
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.

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

Path: workflows/gseapy.cwl

Branch/Commit ID: a0b22644ca178b640fb74849d23b7c631022f0b5
workflow graph Build Bowtie indices

Workflow runs [Bowtie](http://bowtie-bio.sourceforge.net/tutorial.shtml) v1.2.0 (12/30/2016) to build indices for reference genome provided in a single FASTA file as fasta_file input. Generated indices are saved in a folder with the name that corresponds to the input genome

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

Path: workflows/bowtie-index.cwl

Branch/Commit ID: a0b22644ca178b640fb74849d23b7c631022f0b5
workflow graph Apply filters to VCF file

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

Path: definitions/subworkflows/filter_vcf_mouse.cwl

Branch/Commit ID: 195b4ab487c939eb32a55d9f78bc1befd100caae