Explore Workflows

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

Path: src/test/resources/cwl/lobstr-v1/lobSTR-workflow.cwl

Branch/Commit ID: 884ef6f193f41fe713d56871f8b952f2fa20c160

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

Path: task_types/tt_blastn_wnode.cwl

Branch/Commit ID: ac387721a55fd91df3dcdf16e199354618b136d1

Input is a fasta file with n>1 samples, with sample id as sequence identifier prefix, and a sample id file. The workflow calls open otus and assigns taxa using greengenes. The output are taxa plots.

https://github.com/MG-RAST/qiime-pipeline.git

Path: CWL/Workflows/qiime/cluster2plot.cwl

Branch/Commit ID: b8c2be41cd8805023a0d9e5916042b2557205d03

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

Path: tests/wf/sec-wf-out.cwl

Branch/Commit ID: 51516cfa746ab7124c9a512109e53406ea42abcd

Runs RNA-Seq dUTP BioWardrobe basic analysis with strand specific single-end data file.

https://github.com/Barski-lab/workflows.git

Path: workflows/trim-rnaseq-se-dutp.cwl

Branch/Commit ID: 8587882f145d3eb8e258e7bf819a94f8dd666dbf

Runs ChIP-Seq BioWardrobe basic analysis with single-end data file.

https://github.com/Barski-lab/workflows.git

Path: workflows/trim-chipseq-se.cwl

Branch/Commit ID: f371e588940e65889febaea9c35bc96c9e1558c3

Runs RNA-Seq BioWardrobe basic analysis with pair-end data file.

https://github.com/Barski-lab/workflows.git

Path: workflows/rnaseq-pe.cwl

Branch/Commit ID: f371e588940e65889febaea9c35bc96c9e1558c3

Runs DESeq2 using LRT (Likelihood Ratio Test) ============================================= The LRT examines two models for the counts: a full model with a certain number of terms and a reduced model, in which some of the terms of the full model are removed. The test determines if the increased likelihood of the data using the extra terms in the full model is more than expected if those extra terms are truly zero. The LRT is useful for testing multiple terms at once, for example, testing 3 or more levels of a factor at once or all interactions between two variables. The LRT for count data is conceptually similar to an analysis of variance (ANOVA) calculation in linear regression, except that in the case of the Negative Binomial GLM, we use an analysis of deviance (ANODEV), where the deviance captures the difference in likelihood between a full and a reduced model. When performing a likelihood ratio test, the p-values and the test statistic (the 'stat' column) are values for the test that removes all of the variables which are present in the full design and not in the reduced design. This tests the null hypothesis that all the coefficients from these variables and levels of these factors are equal to zero. The likelihood ratio test p-values therefore represent a test of all the variables and all the levels of factors which are among these variables. However, the results table only has space for one column of log fold change, so a single variable and a single comparison is shown (among the potentially multiple log fold changes which were tested in the likelihood ratio test). This indicates that the p-value is for the likelihood ratio test of all the variables and all the levels, while the log fold change is a single comparison from among those variables and levels. **Technical notes** 1. **Biological Replicates:** At least two biological replicates are required for every compared category. 2. **Metadata File:** The metadata file describes relations between compared experiments. For example: ```csv ,time,condition DH1,day5,WT DH2,day5,KO DH3,day7,WT DH4,day7,KO DH5,day7,KO ``` where `time`, `condition`, `day5`, `day7`, `WT`, `KO` should be single words (without spaces), and `DH1`, `DH2`, `DH3`, `DH4`, `DH5` correspond to the experiment aliases set in **RNA-Seq experiments** input. 3. **Design and Reduced Formulas:** Design and reduced formulas should start with `~` and include categories or, optionally, their interactions from the metadata file header. See details in the DESeq2 manual [here](https://bioconductor.org/packages/release/bioc/vignettes/DESeq2/inst/doc/DESeq2.html#interactions) and [here](https://bioconductor.org/packages/release/bioc/vignettes/DESeq2/inst/doc/DESeq2.html#likelihood-ratio-test). 4. **Batch Correction:** If batch correction is required, provide the `batch_file` input. This file should be a headerless TSV/CSV file where the first column contains sample names matching `expression_file_names`, and the second column contains the batch group name.

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

Path: workflows/deseq-lrt-step-1.cwl

Branch/Commit ID: c5f6b511fb0561f5de52fee12a2586c0385e897c

Workflow runs group-isoforms.cwl tool using scatter for isoforms_file input. genes_filename and common_tss_filename inputs are ignored.

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

Path: tools/group-isoforms-batch.cwl

Branch/Commit ID: c5f6b511fb0561f5de52fee12a2586c0385e897c

https://github.com/kids-first/kf-rnaseq-workflow.git

Path: workflow/kfdrc_flagstat_qc.cwl

Branch/Commit ID: 65161d6565c436a7b1e0b3be56efb433a994ed9d