Explore Workflows

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

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

Branch/Commit ID: e9c83739a93fa0b18f8dea2f98b632a9e32725c9

Workflow converts input BAM file into bigWig and bedGraph files. Input BAM file should be sorted by coordinates (required by `bam_to_bedgraph` step). If `split` input is not provided use true by default. Default logic is implemented in `valueFrom` field of `split` input inside `bam_to_bedgraph` step to avoid possible bug in cwltool with setting default values for workflow inputs. `scale` has higher priority over the `mapped_reads_number`. The last one is used to calculate `-scale` parameter for `bedtools genomecov` (step `bam_to_bedgraph`) only in a case when input `scale` is not provided. All logic is implemented inside `bedtools-genomecov.cwl`. `bigwig_filename` defines the output name only for generated bigWig file. `bedgraph_filename` defines the output name for generated bedGraph file and can influence on generated bigWig filename in case when `bigwig_filename` is not provided. All workflow inputs and outputs don't have `format` field to avoid format incompatibility errors when workflow is used as subworkflow.

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

Path: tools/bam-bedgraph-bigwig.cwl

Branch/Commit ID: ce058d892d330125cd03d0a0d5fb3b321cda0be3

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

Path: definitions/pipelines/germline_exome.cwl

Branch/Commit ID: 0c4855bf23622828413ecb09dd30754691c28014

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

Path: definitions/subworkflows/duplex_alignment.cwl

Branch/Commit ID: 3ee63d8757c341ca98b3b46ec4782862ad19b710

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: a68821bf3a9ceadc3b2ffbb535d601d9a645b377

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

Path: definitions/pipelines/aml_trio_cle.cwl

Branch/Commit ID: 3f3b186da9bf82a5e2ae74ba27aef35a46174ebe

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

Path: definitions/subworkflows/docm_germline.cwl

Branch/Commit ID: 3ee63d8757c341ca98b3b46ec4782862ad19b710

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

Path: definitions/subworkflows/varscan_germline.cwl

Branch/Commit ID: 3ee63d8757c341ca98b3b46ec4782862ad19b710

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

Path: definitions/subworkflows/cram_to_bam_and_index.cwl

Branch/Commit ID: 3ee63d8757c341ca98b3b46ec4782862ad19b710

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

Path: task_types/tt_cluster_and_qdump.cwl

Branch/Commit ID: 8ea3637b0f11eac1ea5599c41d74e00d85fb778d