Explore Workflows

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

Path: definitions/subworkflows/cellranger_mkfastq_and_count.cwl

Branch/Commit ID: 6bfb64375e7ebb6eb40f463ede86d8deccdb9eff

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: 2caa50434966ebdf4b33e5ca689c2e4df32f9058

Filters differentially expressed genes from DESeq for Tag Density Profile Analyses ================================================================================== Tool filters output from DESeq pipeline run for genes to create a file with regions of interest for Tag Density Profile Analyses.

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

Path: workflows/filter-deseq-for-heatmap.cwl

Branch/Commit ID: 2caa50434966ebdf4b33e5ca689c2e4df32f9058

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

Path: task_types/tt_cache_asnb_entries.cwl

Branch/Commit ID: 6d04f5d65d1d4893706d9ae7e27341633333054f

This workflow uses MEME suite for motif finding

https://github.com/ncbi/cwl-ngs-workflows-cbb.git

Path: workflows/ChIP-Seq/meme-motif.cwl

Branch/Commit ID: e1c19e64f6fc210f65472ee227786d33c9b4909a

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

Path: task_types/tt_blastn_wnode.cwl

Branch/Commit ID: 909f26beaf96c2cdfe208f87ecd1e9c3de20b81c

https://github.com/NCI-GDC/gdc-dnaseq-cwl.git

Path: workflows/bamfastq_align/extract_readgroup_fastq_pe.cwl

Branch/Commit ID: 20a901f44c9fb0e6f4ee3c40ec33fa4b1c8ef005

Devel version of Single-Cell Cell Ranger Reanalyze ================================================== Workflow calls \"cellranger aggr\" command to rerun secondary analysis performed on the feature-barcode matrix (dimensionality reduction, clustering and visualization) using different parameter settings. As an input we use filtered feature-barcode matrices in HDF5 format from cellranger count or aggr experiments. Note, we don't pass aggregation_metadata from the upstream cellranger aggr step. Need to address this issue when needed.

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

Path: workflows/cellranger-reanalyze.cwl

Branch/Commit ID: a1f6ca50fcb0881781b3ba0306dd61ebf555eaba

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

Path: definitions/pipelines/gathered_cle_somatic_exome.cwl

Branch/Commit ID: 1249b5d4e23d57ca5e3b8ad6d8e5f10ddb019f68

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

Path: tests/wf/1st-workflow.cwl

Branch/Commit ID: 3ed10d0ea7ac57550433a89a92bdbe756bdb0e40