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Graph Name Retrieved From View
workflow graph 03-map-pe.cwl

ATAC-seq 03 mapping - reads: PE

https://github.com/Duke-GCB/GGR-cwl.git

Path: v1.0/ATAC-seq_pipeline/03-map-pe.cwl

Branch/Commit ID: 8aabde14169421a7115c5cd48c4740b3a7bd818f

workflow graph 5S-from-tablehits.cwl

https://github.com/proteinswebteam/ebi-metagenomics-cwl.git

Path: tools/5S-from-tablehits.cwl

Branch/Commit ID: 25129f55226dee595ef941edc24d3c44414e0523

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: c9e7f3de7f6ba38ee663bd3f9649e8d7dbac0c86

workflow graph THOR - differential peak calling of ChIP-seq signals with replicates

What is THOR? -------------- THOR is an HMM-based approach to detect and analyze differential peaks in two sets of ChIP-seq data from distinct biological conditions with replicates. THOR performs genomic signal processing, peak calling and p-value calculation in an integrated framework. For more information please refer to: ------------------------------------- Allhoff, M., Sere K., Freitas, J., Zenke, M., Costa, I.G. (2016), Differential Peak Calling of ChIP-seq Signals with Replicates with THOR, Nucleic Acids Research, epub gkw680.

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

Path: workflows/rgt-thor.cwl

Branch/Commit ID: 8049a781ac4aae579fbd3036fa0bf654532f15be

workflow graph sec-wf-out.cwl

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

Path: tests/wf/sec-wf-out.cwl

Branch/Commit ID: 07ebbea2bdf97955060c1dd563580b386388519b

workflow graph Execute CRISPR

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

Path: bacterial_mobile_elem/wf_bacterial_mobile_elem.cwl

Branch/Commit ID: e2a6cbcc36212433d8fbc804919442787a5e2a49

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: 799575ce58746813f066a665adeacdda252d8cab

workflow graph tt_univec_wnode.cwl

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

Path: task_types/tt_univec_wnode.cwl

Branch/Commit ID: e2a6cbcc36212433d8fbc804919442787a5e2a49

workflow graph fail-unconnected.cwl

https://github.com/common-workflow-language/cwl-v1.1.git

Path: tests/fail-unconnected.cwl

Branch/Commit ID: 6397014050177074c9ccd0d771577f7fa9f728a3

workflow graph 1st-workflow.cwl

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

Path: _includes/cwl/22-nested-workflows/1st-workflow.cwl

Branch/Commit ID: fb086088825d19c1136b97dd5997a060da8d44d6