Explore Workflows

https://github.com/GusEllerm/CWL_workflows.git

Path: workflows/BEAST_examples/beast-2step-workflow.cwl

Branch/Commit ID: 3b6b802c616609bdd39d8fafb8a14dd82e5cb17a

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: 664de58d95728edbf7d369d894f9037ebe2475fa

https://github.com/NCI-GDC/aliquot-maf-cwl.git

Path: vcf-to-aliquot-maf/subworkflows/extract_file_with_index.cwl

Branch/Commit ID: 9aedc3fb22a3f5b9146bc5e9a393085050f90c95

https://github.com/ebi-wp/webservice-cwl.git

Path: workflows/workflow-phmmer-blast.cwl

Branch/Commit ID: 88b9948c4977ca90ab5ceb391b2235043135480d

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

Path: definitions/pipelines/alignment_wgs.cwl

Branch/Commit ID: 2e298960837739717ec2928a99c5d811183012e6

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

Path: spurious_annot/wf_spurious_annot_pass1.cwl

Branch/Commit ID: c009eeba7379efbbd37b8d5013a83f161f06939b

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

Path: tests/count-lines14-wf.cwl

Branch/Commit ID: 57baec040c99d7edef8242ef51b5470b1c82d733

GATK4.1.2 Mutect2 workflow

https://github.com/nci-gdc/gatk4_mutect2_cwl.git

Path: subworkflows/mutect2_calling.cwl

Branch/Commit ID: 138d484362084dfc97d9fb7d839855b4bc2c5599

https://github.com/hubmapconsortium/sc-atac-seq-pipeline.git

Path: bulk-atac-seq-pipeline.cwl

Branch/Commit ID: fab00c3064b4841ac587d9a4698b6f56fa6f3fca

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

Path: task_types/tt_kmer_seq_entry_extract_wnode.cwl

Branch/Commit ID: 546742b523ce12f6246a52c838a51920a08dad4b