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Graph Name Retrieved From View
workflow graph bact_get_kmer_reference

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

Path: task_types/tt_bact_get_kmer_reference.cwl

Branch/Commit ID: 8ea3637b0f11eac1ea5599c41d74e00d85fb778d
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: ce058d892d330125cd03d0a0d5fb3b321cda0be3
workflow graph magicblast-alignment-pe

This workflow aligns the fastq files using magicblast for paired-end samples

 https://github.com/ncbi/cwl-ngs-workflows-cbb.git

Path: workflows/Alignments/magicblast-alignment.cwl

Branch/Commit ID: 0e21d424267367d9dae7b980438ddee14c31a445
workflow graph Unaligned to aligned BAM

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

Path: definitions/subworkflows/align.cwl

Branch/Commit ID: 3ee63d8757c341ca98b3b46ec4782862ad19b710
workflow graph timelimit4-wf.cwl

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

Path: tests/timelimit4-wf.cwl

Branch/Commit ID: 57baec040c99d7edef8242ef51b5470b1c82d733
workflow graph Detect DoCM variants

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

Path: definitions/subworkflows/docm_germline.cwl

Branch/Commit ID: a9133c999502acf94b433af8d39897e6c2cdf65f
workflow graph scatter-wf1.cwl

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

Path: cwltool/schemas/v1.0/v1.0/scatter-wf1.cwl

Branch/Commit ID: 2ae8117360a3cd4909d9d3f2b35c30bfffb25d0a
workflow graph tt_univec_wnode.cwl

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

Path: task_types/tt_univec_wnode.cwl

Branch/Commit ID: 8ea3637b0f11eac1ea5599c41d74e00d85fb778d
workflow graph wgs alignment with qc

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

Path: definitions/pipelines/wgs_alignment.cwl

Branch/Commit ID: 3ee63d8757c341ca98b3b46ec4782862ad19b710
workflow graph PGAP Pipeline

PGAP pipeline for external usage, powered via containers

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

Path: wf_common.cwl

Branch/Commit ID: 8ea3637b0f11eac1ea5599c41d74e00d85fb778d