Explore Workflows

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Graph Name Retrieved From View
workflow graph main-wes_chr21_test.cwl

https://github.com/bcbio/bcbio_validation_workflows.git

Path: wes-agha-test/wes_chr21_test-workflow-arvados/main-wes_chr21_test.cwl

Branch/Commit ID: af9a5621efcb44c249697d6df071fe4defe389ac
workflow graph tmb_workflow.cwl

Workflow to run the TMB analysis on a batch of samples and merge the results back into a single data clinical file

https://github.com/mskcc/pluto-cwl.git

Path: cwl/tmb_workflow.cwl

Branch/Commit ID: 7eb2b0a4d37018142233d770595ac2e00376dab4
workflow graph tt_kmer_compare_wnode

Pairwise comparison

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

Path: task_types/tt_kmer_compare_wnode.cwl

Branch/Commit ID: 94c97cfc95a5bf102a6f9206e045ea1afb768317
workflow graph Chipseq alignment with qc and creating homer tag directory

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

Path: definitions/pipelines/chipseq.cwl

Branch/Commit ID: a08de598edc04f340fdbff76c9a92336a7702022
workflow graph gcaccess_from_list

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

Path: task_types/tt_gcaccess_from_list.cwl

Branch/Commit ID: e3f18c61d1bbf65e40921dbd044369da4523ee3e
workflow graph DiffBind - Differential Binding Analysis of ChIP-Seq Peak Data

Differential Binding Analysis of ChIP-Seq Peak Data --------------------------------------------------- DiffBind processes ChIP-Seq data enriched for genomic loci where specific protein/DNA binding occurs, including peak sets identified by ChIP-Seq peak callers and aligned sequence read datasets. It is designed to work with multiple peak sets simultaneously, representing different ChIP experiments (antibodies, transcription factor and/or histone marks, experimental conditions, replicates) as well as managing the results of multiple peak callers. For more information please refer to: ------------------------------------- Ross-Innes CS, Stark R, Teschendorff AE, Holmes KA, Ali HR, Dunning MJ, Brown GD, Gojis O, Ellis IO, Green AR, Ali S, Chin S, Palmieri C, Caldas C, Carroll JS (2012). “Differential oestrogen receptor binding is associated with clinical outcome in breast cancer.” Nature, 481, -4.

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

Path: workflows/diffbind.cwl

Branch/Commit ID: 104059e07a2964673e21d371763e33c0afeb2d03
workflow graph HBA_target.cwl

https://git.astron.nl/eosc/prefactor3-cwl.git

Path: workflows/HBA_target.cwl

Branch/Commit ID: 6633c39d59a81b9ebf8312450bf50d6a0fe66efa
workflow graph Run pindel on provided region

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

Path: definitions/subworkflows/pindel_region.cwl

Branch/Commit ID: a08de598edc04f340fdbff76c9a92336a7702022
workflow graph CNV_FPS

https://gitlab.bsc.es/lrodrig1/structuralvariants_poc.git

Path: structuralvariants/workflow.cwl

Branch/Commit ID: 0864e19de6a1732a1376c6a64a93794d2fc45d23
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: 104059e07a2964673e21d371763e33c0afeb2d03