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Graph Name Retrieved From View
workflow graph MAnorm PE - quantitative comparison of ChIP-Seq paired-end 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 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: ee66d03be8a7fd61367db40c37a973ff55ece4da
workflow graph genomel_cohort_gatk4.cwl

https://github.com/uc-cdis/genomel_pipelines.git

Path: genomel/genomel_cohort_gatk4.cwl

Branch/Commit ID: 13c106834d6c9031de08496faeff521740a0c95f
workflow graph gathered exome alignment and somatic variant detection

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

Path: definitions/pipelines/gathered_somatic_exome.cwl

Branch/Commit ID: 1249b5d4e23d57ca5e3b8ad6d8e5f10ddb019f68
workflow graph xenbase-rnaseq-se.cwl

XenBase workflow for analysing RNA-Seq single-end data

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

Path: workflows/xenbase-rnaseq-se.cwl

Branch/Commit ID: 94471ee6c01b7bc17102e45e56e7366c2a52acdf
workflow graph wgs alignment and tumor-only variant detection

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

Path: definitions/pipelines/tumor_only_wgs.cwl

Branch/Commit ID: 889a077a20c0fdb01f4ed97aa4bc40f920c37a1a
workflow graph Exome QC workflow

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

Path: definitions/subworkflows/qc_exome.cwl

Branch/Commit ID: 295e7b7f51727c0f2d6cc86ce817449b2e8dba3c
workflow graph Salmon quantification, FASTQ -> H5AD count matrix

https://github.com/hubmapconsortium/salmon-rnaseq.git

Path: steps/salmon-quantification.cwl

Branch/Commit ID: 14d004a163e02a5f8f8590e568a2f4f153508931
workflow graph tt_univec_wnode.cwl

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

Path: task_types/tt_univec_wnode.cwl

Branch/Commit ID: 146df33e2e44afa2a608ac72c036e6b6b871af93
workflow graph Filter differentially expressed genes from DESeq for Tag Density Profile Analyses

Filters differentially expressed genes from DESeq for Tag Density Profile Analyses ================================================================================== Tool filters output from DESeq pipeline run for genes to create a file with regions of interest for Tag Density Profile Analyses.

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

Path: workflows/filter-deseq-for-heatmap.cwl

Branch/Commit ID: a1f6ca50fcb0881781b3ba0306dd61ebf555eaba
workflow graph scatter-wf4.cwl#main

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

Path: tests/wf/scatter-wf4.cwl

Branch/Commit ID: 5ae5798f1c0c8d2178986b77cfd74edff510877a

Packed ID: main