Explore Workflows

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

Graph Name Retrieved From View
workflow graph iwdr_with_nested_dirs.cwl

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

Path: cwltool/schemas/v1.0/v1.0/iwdr_with_nested_dirs.cwl

Branch/Commit ID: 6003cbb94f16103241b562f2133e7c4acac6c621
workflow graph Cell Ranger Aggregate (RNA+ATAC)

Cell Ranger Aggregate (RNA+ATAC) Combines outputs from multiple runs of “Cell Ranger Count (RNA+ATAC)” pipeline. The results of this workflow are primarily used in “Single-Cell Multiome ATAC and RNA-Seq Filtering Analysis” pipeline.

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

Path: workflows/cellranger-arc-aggr.cwl

Branch/Commit ID: 3a311af320e65271f3efb4f27a6ed10aa5d50a0e
workflow graph adapter for sequence_align_and_tag

Some workflow engines won't stage files in our nested structure, so parse it out here

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

Path: definitions/subworkflows/sequence_align_and_tag_adapter.cwl

Branch/Commit ID: 7b4b489474473c3d2d992a838b89632c2b97dc2c
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: efb40a812cdba2df6699f130ee5aeea9b63045cd

Packed ID: collision
workflow graph MAnorm SE - quantitative comparison of ChIP-Seq single-read data

What is MAnorm? -------------- MAnorm is a robust model for quantitative comparison of ChIP-Seq data sets of TFs (transcription factors) or epigenetic modifications and you can use it for: * Normalization of two ChIP-seq samples * Quantitative comparison (differential analysis) of two ChIP-seq samples * Evaluating the overlap enrichment of the protein binding sites(peaks) * Elucidating underlying mechanisms of cell-type specific gene regulation How MAnorm works? ---------------- MAnorm uses common peaks of two samples as a reference to build the rescaling model for normalization, which is based on the empirical assumption that if a chromatin-associated protein has a substantial number of peaks shared in two conditions, the binding at these common regions will tend to be determined by similar mechanisms, and thus should exhibit similar global binding intensities across samples. The observed differences on common peaks are presumed to reflect the scaling relationship of ChIP-Seq signals between two samples, which can be applied to all peaks. What do the inputs mean? ---------------- ### General **Experiment short name/Alias** * short name for you experiment to identify among the others **ChIP-Seq SE sample 1** * previously analyzed ChIP-Seq single-read experiment to be used as Sample 1 **ChIP-Seq SE sample 2** * previously analyzed ChIP-Seq single-read experiment to be used as Sample 2 **Genome** * Reference genome to be used for gene assigning ### Advanced **Reads shift size for sample 1** * This value is used to shift reads towards 3' direction to determine the precise binding site. Set as half of the fragment length. Default 100 **Reads shift size for sample 2** * This value is used to shift reads towards 5' direction to determine the precise binding site. Set as half of the fragment length. Default 100 **M-value (log2-ratio) cutoff** * Absolute M-value (log2-ratio) cutoff to define biased (differential binding) peaks. Default: 1.0 **P-value cutoff** * P-value cutoff to define biased peaks. Default: 0.01 **Window size** * Window size to count reads and calculate read densities. 2000 is recommended for sharp histone marks like H3K4me3 and H3K27ac, and 1000 for TFs or DNase-seq. Default: 2000

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

Path: workflows/manorm-se.cwl

Branch/Commit ID: 2caa50434966ebdf4b33e5ca689c2e4df32f9058
workflow graph Run genomic CMsearch

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

Path: bacterial_noncoding/wf_gcmsearch.cwl

Branch/Commit ID: 17bae57a1f00f5c6db8f3a82d86262f12b8153cf
workflow graph exome alignment and somatic variant detection for cle purpose

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

Path: definitions/pipelines/somatic_exome_cle.cwl

Branch/Commit ID: 22fce2dbdada0c4135b6f0677f78535cf980cb07
workflow graph WGS and MT analysis for fastq files

rna / protein - qc, preprocess, filter, annotation, index, abundance

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

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

Branch/Commit ID: 6a8727124baf77416ca797982fd4e0689c2a593a
workflow graph scatter-valuefrom-wf3.cwl#main

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

Path: cwltool/schemas/v1.0/v1.0/scatter-valuefrom-wf3.cwl

Branch/Commit ID: 4c905b830371eee45188a53510ba0ee9113fd4c8

Packed ID: main
workflow graph Apply filters to VCF file

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

Path: definitions/subworkflows/germline_filter_vcf.cwl

Branch/Commit ID: 31a179d7a2f2ac86bfd7fcc4dc79832c3739ae76