Explore Workflows

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

Path: tests/wf/sec-wf.cwl

Branch/Commit ID: 0e98de8f692bb7b9626ed44af835051750ac20cd

https://github.com/uc-cdis/genomel_pipelines.git

Path: genomel/cwl/workflows/utils/duplicated_readgroup_fix.cwl

Branch/Commit ID: f83b0e3d2ab7a29a0425bf25b5bae68c3dc70999

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

Path: tests/fail-unconnected.cwl

Branch/Commit ID: 5f27e234b4ca88ed1280dedf9e3391a01de12912

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

Path: v1.0/v1.0/dynresreq-workflow-inputdefault.cwl

Branch/Commit ID: 1f501e38ff692a408e16b246ac7d64d32f0822c2

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: 91bb63948c0a264334b9007ef85f936768d90d11

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

Path: subworkflows/xenbase-fastq-bowtie-bigwig-se-pe.cwl

Branch/Commit ID: fb355eda4555a7e7182a91ce045212b0a087d73f

The original [BioWardrobe's](https://biowardrobe.com) [PubMed ID:26248465](https://www.ncbi.nlm.nih.gov/pubmed/26248465) **RNA-Seq** basic analysis for a **paired-end** experiment. A corresponded input [FASTQ](http://maq.sourceforge.net/fastq.shtml) file has to be provided. Current workflow should be used only with the paired-end RNA-Seq data. It performs the following steps: 1. Use STAR to align reads from input FASTQ files according to the predefined reference indices; generate unsorted BAM file and alignment statistics file 2. Use fastx_quality_stats to analyze input FASTQ files and generate quality statistics files 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) 4. Generate BigWig file on the base of sorted BAM file 5. Map input FASTQ files to predefined rRNA reference indices using Bowtie to define the level of rRNA contamination; export resulted statistics to file 6. 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.cwl

Branch/Commit ID: 2cad55523d1b4ee7fd9e64df0f6263c6545e4b0e

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

Path: subworkflows/xenbase-sra-to-fastq-se.cwl

Branch/Commit ID: 877546bb89b793cc8830f8d803858706937a654b

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 therefore 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 one performs 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. At least two biological replicates are required for every compared category 2. Metadata file describes relations between compared experiments, for example ``` ,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 a 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 should start with **~** and include categories or, optionally, their interactions from the metadata file header. See details in 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. Contrast should be set based on your metadata file header and available categories in a form of `Factor Numerator Denominator`, where `Factor` - column name from metadata file, `Numerator` - category from metadata file to be used as numerator in fold change calculation, `Denominator` - category from metadata file to be used as denominator in fold change calculation. For example `condition WT KO`.

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

Path: workflows/deseq-lrt.cwl

Branch/Commit ID: 8049a781ac4aae579fbd3036fa0bf654532f15be

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

Path: subworkflows/xenbase-fastq-bowtie-bigwig-se-pe.cwl

Branch/Commit ID: c602e3cdd72ff904dd54d46ba2b5146eb1c57022