Explore Workflows

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

Path: metadata/chipseq-header.cwl

Branch/Commit ID: 261c0232a7a40880f2480b811ed2d7e89c463869

https://github.com/Marco-Salvi/cwl-test.git

Path: wf5301/workflow.cwl

Branch/Commit ID: 0e6cfe0646173e228b2fce63e23ed8f9d78598b0

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

Path: tests/count-lines11-wf-noET.cwl

Branch/Commit ID: 31ec48a8d81ef7c1b2c5e9c0a19e7623efe4a1e2

Workflow converts input BAM file into bigWig and bedGraph files. Input BAM file should be sorted by coordinates (required by `bam_to_bedgraph` step). If `split` input is not provided use true by default. Default logic is implemented in `valueFrom` field of `split` input inside `bam_to_bedgraph` step to avoid possible bug in cwltool with setting default values for workflow inputs. `scale` has higher priority over the `mapped_reads_number`. The last one is used to calculate `-scale` parameter for `bedtools genomecov` (step `bam_to_bedgraph`) only in a case when input `scale` is not provided. All logic is implemented inside `bedtools-genomecov.cwl`. `bigwig_filename` defines the output name only for generated bigWig file. `bedgraph_filename` defines the output name for generated bedGraph file and can influence on generated bigWig filename in case when `bigwig_filename` is not provided. All workflow inputs and outputs don't have `format` field to avoid format incompatibility errors when workflow is used as subworkflow.

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

Path: tools/bam-bedgraph-bigwig.cwl

Branch/Commit ID: 8f5444418aad3424ccb05a3e618bd773f99f8e6e

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

Path: tests/wf-loadContents4.cwl

Branch/Commit ID: 31ec48a8d81ef7c1b2c5e9c0a19e7623efe4a1e2

This workflow creates a subsample from a BAM file creating a tagAlign and pseudoreplicates

https://github.com/ncbi/cwl-ngs-workflows-cbb.git

Path: workflows/File-formats/subample-pseudoreplicates.cwl

Branch/Commit ID: 33123d6a92bf0038951820d0d2c9cf501ae2ebf6

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

Path: testdata/workflow_input_sf_expr_v1_2.cwl

Branch/Commit ID: 77669d4dd1d1ebd2bdd9810f911608146d9b8e51

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 PE sample 1** * previously analyzed ChIP-Seq paired-end experiment to be used as Sample 1 **ChIP-Seq PE sample 2** * previously analyzed ChIP-Seq paired-end 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-pe.cwl

Branch/Commit ID: 2b8146f76595f0c4d8bf692de78b21280162b1d0

Single-Cell ATAC-Seq Genome Coverage Generates genome coverage tracks from chromatin accessibility data of selected cells

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

Path: workflows/sc-atac-coverage.cwl

Branch/Commit ID: 261c0232a7a40880f2480b811ed2d7e89c463869

https://github.com/NCGM-genome/WGSpipeline.git

Path: Workflows/germline-gpu-v4.0.1.cwl

Branch/Commit ID: b8262067df44ce67268f8af00a043f2187c604bb