Explore Workflows

https://github.com/rawgene/cwl.git

Path: workflows/star_samtools_stringtie-prepDE-DESeq2.htseq-dexseq.cwl

Branch/Commit ID: 33a3cdba1184ad14e7a168eef3c505b9b4332f47

Single-cell Pseudobulk Differential Expression Analysis Between Datasets Identifies differentially expressed genes between groups of cells coerced to pseudobulk datasets.

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

Path: workflows/sc-rna-de-pseudobulk.cwl

Branch/Commit ID: 36fd18f11e939d3908b1eca8d2939402f7a99b0f

Note: should be updated The original [BioWardrobe's](https://biowardrobe.com) [PubMed ID:26248465](https://www.ncbi.nlm.nih.gov/pubmed/26248465) **RNA-Seq** basic analysis for **strand specific single-read** experiment. A corresponded input [FASTQ](http://maq.sourceforge.net/fastq.shtml) file has to be provided. Current workflow should be used only with the single-read RNA-Seq data. It performs the following steps: 1. Use STAR to align reads from input FASTQ file according to the predefined reference indices; generate unsorted BAM file and alignment statistics file 2. Use fastx_quality_stats to analyze input FASTQ file and generate quality statistics file 3. Use samtools sort to generate coordinate sorted BAM(+BAI) file pair from the unsorted BAM file obtained on the step 1 (after running STAR) 5. Generate BigWig file on the base of sorted BAM file 6. Map input FASTQ file to predefined rRNA reference indices using Bowtie to define the level of rRNA contamination; export resulted statistics to file 7. Calculate isoform expression level for the sorted BAM file and GTF/TAB annotation file using GEEP reads-counting utility; export results to file

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

Path: workflows/rnaseq-se-dutp.cwl

Branch/Commit ID: 42dc4f70b117e78785b82865ec4c4b941ac1c259

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

Path: definitions/subworkflows/bam_to_trimmed_fastq.cwl

Branch/Commit ID: 0c4f4e59c265eb22aed3d2d37b173cb5430773d2

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: cd1ba3df3745fba4b635f05c67ebeaf3b8a9f4ec

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: 4106b7dc96e968db291b7a61ecd1641aa3b3dd6d

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

Path: definitions/subworkflows/bam_to_trimmed_fastq_and_biscuit_alignments.cwl

Branch/Commit ID: 60edaf6f57eaaf02cda1a3d8cb9a825aa64a43e2

https://github.com/common-workflow-language/cwl-v1.1.git

Path: tests/scatter-valuefrom-inputs-wf1.cwl

Branch/Commit ID: 50251ef931d108c09bed2d330d3d4fe9c562b1c3

https://github.com/ResearchObject/runcrate.git

Path: tests/data/no-output-run-1/snapshot/wf.cwl

Branch/Commit ID: 44c831fb97958470d88efc8ecf7ff09bfa2c4e1a

https://github.com/CRI-iAtlas/iatlas-workflows.git

Path: Kallisto/workflow/kallisto_scatter_synapse_single_end_workflow.cwl

Branch/Commit ID: c7fa0fa9ef94c657b664f680462dbc3f5b7a32e8