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Graph Name Retrieved From View
workflow graph kmer_ref_compare_wnode

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

Path: task_types/tt_kmer_ref_compare_wnode.cwl

Branch/Commit ID: 424a01693259a75641dc249d553235aa38a6ce23
workflow graph timelimit2-wf.cwl

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

Path: tests/timelimit2-wf.cwl

Branch/Commit ID: 31ec48a8d81ef7c1b2c5e9c0a19e7623efe4a1e2
workflow graph step_valuefrom5_wf_with_id_v1_2.cwl

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

Path: testdata/step_valuefrom5_wf_with_id_v1_2.cwl

Branch/Commit ID: b76b039edb62dea76c43f173848cdc57e4b4aab7
workflow graph Detect Docm variants

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

Path: definitions/subworkflows/docm_cle.cwl

Branch/Commit ID: 293dc7b83639d21a56efff2baf9dfe4e97b9b806
workflow graph stdout-wf_v1_0.cwl

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

Path: testdata/stdout-wf_v1_0.cwl

Branch/Commit ID: b76b039edb62dea76c43f173848cdc57e4b4aab7
workflow graph RNA-Seq pipeline single-read stranded mitochondrial

Slightly changed 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. An additional steps were added to map data to mitochondrial chromosome only and then merge the output. Experiment files in [FASTQ](http://maq.sourceforge.net/fastq.shtml) format either compressed or not can be used. Current workflow should be used only with single-read strand specific RNA-Seq data. It performs the following steps: 1. `STAR` to align reads from input FASTQ file according to the predefined reference indices; generate unsorted BAM file and alignment statistics file 2. `fastx_quality_stats` to analyze input FASTQ file and generate quality statistics file 3. `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-mitochondrial.cwl

Branch/Commit ID: 93b844a80f4008cc973ea9b5efedaff32a343895
workflow graph DESeq2 (LRT, step 1) - differential gene expression analysis using likelihood ratio test

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: db880986ee60b3594b7d9a9f278199bb4a9227d5
workflow graph RNA-Seq pipeline paired-end stranded mitochondrial

Slightly changed original [BioWardrobe's](https://biowardrobe.com) [PubMed ID:26248465](https://www.ncbi.nlm.nih.gov/pubmed/26248465) **RNA-Seq** basic analysis for **strand specific pair-end** experiment. An additional steps were added to map data to mitochondrial chromosome only and then merge the output. Experiment files in [FASTQ](http://maq.sourceforge.net/fastq.shtml) format either compressed or not can be used. Current workflow should be used only with the pair-end strand specific RNA-Seq data. It performs the following steps: 1. `STAR` to align reads from input FASTQ file according to the predefined reference indices; generate unsorted BAM file and alignment statistics file 2. `fastx_quality_stats` to analyze input FASTQ file and generate quality statistics file 3. `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-pe-dutp-mitochondrial.cwl

Branch/Commit ID: 93b844a80f4008cc973ea9b5efedaff32a343895
workflow graph Prepare user input

Prepare user input for NCBI-PGAP pipeline

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

Path: prepare_user_input2.cwl

Branch/Commit ID: 424a01693259a75641dc249d553235aa38a6ce23
workflow graph scRNA-seq pipeline using Salmon and Alevin

https://github.com/hubmapconsortium/salmon-rnaseq.git

Path: pipeline.cwl

Branch/Commit ID: f8ea70d9461bd496f0a8f82ca450fca900b6972c