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Graph Name Retrieved From View
workflow graph fillout_workflow.cwl

Workflow to run GetBaseCountsMultiSample fillout on a number of bam files with a single maf file

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

Path: cwl/fillout_workflow.cwl

Branch/Commit ID: 5cad957fec135aa55ca8d588372db0557ca1cad5
workflow graph DESeq - differential gene expression analysis

Differential gene expression analysis ===================================== Differential gene expression analysis based on the negative binomial distribution Estimate variance-mean dependence in count data from high-throughput sequencing assays and test for differential expression based on a model using the negative binomial distribution. DESeq1 ------ High-throughput sequencing assays such as RNA-Seq, ChIP-Seq or barcode counting provide quantitative readouts in the form of count data. To infer differential signal in such data correctly and with good statistical power, estimation of data variability throughout the dynamic range and a suitable error model are required. Simon Anders and Wolfgang Huber propose a method based on the negative binomial distribution, with variance and mean linked by local regression and present an implementation, [DESeq](http://bioconductor.org/packages/release/bioc/html/DESeq.html), as an R/Bioconductor package DESeq2 ------ In comparative high-throughput sequencing assays, a fundamental task is the analysis of count data, such as read counts per gene in RNA-seq, for evidence of systematic changes across experimental conditions. Small replicate numbers, discreteness, large dynamic range and the presence of outliers require a suitable statistical approach. [DESeq2](http://www.bioconductor.org/packages/release/bioc/html/DESeq2.html), a method for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates. This enables a more quantitative analysis focused on the strength rather than the mere presence of differential expression.

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

Path: workflows/deseq.cwl

Branch/Commit ID: 261c0232a7a40880f2480b811ed2d7e89c463869
workflow graph count-lines6-wf.cwl

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

Path: tests/count-lines6-wf.cwl

Branch/Commit ID: 707ebcd2173889604459c5f4ffb55173c508abb3
workflow graph echo-wf-default.cwl

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

Path: tests/echo-wf-default.cwl

Branch/Commit ID: 707ebcd2173889604459c5f4ffb55173c508abb3
workflow graph count-lines13-wf.cwl

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

Path: cwltool/schemas/v1.0/v1.0/count-lines13-wf.cwl

Branch/Commit ID: 5ef2516220cd2ed327ba7966e7d812de969f4eea
workflow graph mut3.cwl

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

Path: tests/wf/mut3.cwl

Branch/Commit ID: 3ed10d0ea7ac57550433a89a92bdbe756bdb0e40
workflow graph extract_gencoll_ids

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

Path: task_types/tt_extract_gencoll_ids.cwl

Branch/Commit ID: a2d6cd4c53bf3501f6bd79edebb7ca30bba8456f
workflow graph Workflow to run pVACseq from detect_variants and rnaseq pipeline outputs

https://github.com/tmooney/cancer-genomics-workflow.git

Path: definitions/subworkflows/pvacseq.cwl

Branch/Commit ID: 0db1a5f1ceedd4416ac550787c27b99c87dbe985
workflow graph exome alignment and germline variant detection

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

Path: definitions/pipelines/germline_exome.cwl

Branch/Commit ID: b9e7392e72506cadd898a6ac4db330baf6535ab6
workflow graph taxonomy_check_16S

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

Path: task_types/tt_taxonomy_check_16S.cwl

Branch/Commit ID: 61e3752f1f5e2ee498fa024c235226f8580be942