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Graph Name Retrieved From View
workflow graph AltAnalyze Build Reference Indices

AltAnalyze Build Reference Indices ==================================

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

Path: workflows/altanalyze-prepare-genome.cwl

Branch/Commit ID: 581156366f91861bd4dbb5bcb59f67d468b32af3

workflow graph extract_amplicon_kit_http.cwl

https://github.com/nci-gdc/gdc-dnaseq-cwl.git

Path: workflows/bamfastq_align/extract_amplicon_kit_http.cwl

Branch/Commit ID: 2f7c0e92e7b88b57b86602f11c595661c374008a

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: 8bf36bfad5624fbc8fc315e82783a44e9e5e4470

workflow graph msa.cwl

https://github.com/common-workflow-lab/2020-covid-19-bh.git

Path: msa/msa.cwl

Branch/Commit ID: 8fd2d9814a5641a55efd8e63fa65a652b66f9d0b

workflow graph count-lines10-wf.cwl

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

Path: cwltool/schemas/v1.0/v1.0/count-lines10-wf.cwl

Branch/Commit ID: 0db44e3c9805a070564f954222efff71cd791b70

workflow graph revsort.cwl

Reverse the lines in a document, then sort those lines.

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

Path: tests/wf/revsort.cwl

Branch/Commit ID: 0e8110083bad6ea98fc487aa262953a6c5e010b5

workflow graph BlastP_RBH_workflow

https://github.com/ncbi/cwl-demos.git

Path: blast-pipelines/blast_workflow.cwl

Branch/Commit ID: 496b3e2bff8c20d5a7d5c3cbe9b64697767b1c13

workflow graph Cell Ranger Build Reference Indices

Cell Ranger Build Reference Indices ===================================

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

Path: workflows/cellranger-mkref.cwl

Branch/Commit ID: 1a46cb0e8f973481fe5ae3ae6188a41622c8532e

workflow graph default-wf5.cwl

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

Path: tests/wf/default-wf5.cwl

Branch/Commit ID: 1441c285e8a5afe399f5d52ca9059cb8bb513edb

workflow graph scatter-valuefrom-wf2.cwl

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

Path: cwltool/schemas/v1.0/v1.0/scatter-valuefrom-wf2.cwl

Branch/Commit ID: 26870e38cec81af880cd3e4789ae6cee8fc27020