Explore Workflows

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

Path: subworkflows/allele-process-reference.cwl

Branch/Commit ID: 9b4dc225c537685b9c9a32d931d3892d20953dd7

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: b4d578c2ba4713a5a22163d9f8c7105acda1f22e

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

Path: testdata/scatter-wf1_v1_2.cwl

Branch/Commit ID: e949503ac0dd7e22ba9b04ac51926d13780f9cee

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

Path: tests/timelimit-wf.cwl

Branch/Commit ID: 31ec48a8d81ef7c1b2c5e9c0a19e7623efe4a1e2

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

Path: testdata/scatter-wf3_v1_1.cwl

Branch/Commit ID: e949503ac0dd7e22ba9b04ac51926d13780f9cee

Packed ID: main

https://github.com/peijin94/LOFAR-Sun-tools.git

Path: utils/IM/LINC/lincSun/workflow/calibrator_sun.cwl

Branch/Commit ID: f44502475496d46a6cde17b9881aa19d852debfb

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

Path: definitions/subworkflows/germline_detect_variants.cwl

Branch/Commit ID: 641083e9ed933d388f36fa04c00c20a810599e94

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: 954bb2f213d97dfef1cddaf9e830169a92ad0c6b

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

Path: testdata/workflow_input_sf_expr.cwl

Branch/Commit ID: e949503ac0dd7e22ba9b04ac51926d13780f9cee

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

Path: task_types/tt_fscr_calls_pass1.cwl

Branch/Commit ID: 16e3915d2a357e2a861b30911c832e5ddc0c1784