Explore Workflows
View already parsed workflows here or click here to add your own
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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: dda9e6e06a656b7b3fa7504156474b962fe3953c |
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blastp_wnode_naming
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https://github.com/ncbi/pgap.git
Path: task_types/tt_blastp_wnode_naming.cwl Branch/Commit ID: 1b8d71c75156a1a62bf0477d59db26010e2dcc29 |
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extract_gencoll_ids
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https://github.com/ncbi/pgap.git
Path: task_types/tt_extract_gencoll_ids.cwl Branch/Commit ID: 550682d2fe3348161eab1b8612e48a59af4ac6a5 |
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mut.cwl
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https://github.com/common-workflow-language/cwltool.git
Path: tests/wf/mut.cwl Branch/Commit ID: b82ce7ae901a54c7a062fd5eefd8d5ceb5a4d684 |
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phase VCF
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https://github.com/genome/analysis-workflows.git
Path: definitions/subworkflows/phase_vcf.cwl Branch/Commit ID: d2c2f2eb846ae2e9cdcab46e3bb88e42126cb3f5 |
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facets-workflow.cwl
Workflow for running Facets-suite on a set of tumor normal pairs This workflow scatters over all the pairs in the input JSON to run all samples in parallel Input JSON format ----------------- { \"pairs\": [ { \"tumor_bam\": { \"class\": \"File\", \"path\": \"/test_data/bam/Tumor1.rg.md.abra.printreads.bam\" }, \"normal_bam\": { \"class\": \"File\", \"path\": \"/test_data/bam/Normal1.rg.md.abra.printreads.bam\" }, \"pair_maf\": { \"class\": \"File\", \"path\": \"/test_data/bam/Tumor1.Normal1.maf\" }, \"pair_id\": \"Tumor1.Normal1\" }, { \"tumor_bam\": { \"class\": \"File\", \"path\": \"/test_data/bam/Tumor2.rg.md.abra.printreads.bam\" }, \"normal_bam\": { \"class\": \"File\", \"path\": \"/test_data/bam/Normal2.rg.md.abra.printreads.bam\" }, \"pair_maf\": { \"class\": \"File\", \"path\": \"/test_data/bam/Tumor2.Normal2.maf\" }, \"pair_id\": \"Tumor2.Normal2\" } ] } Output format ------------- output └── facets-suite ├── Tumor1.Normal1.arm_level.txt ├── Tumor1.Normal1.gene_level.txt ├── Tumor1.Normal1_hisens.ccf.maf ├── Tumor1.Normal1_hisens.rds ├── Tumor1.Normal1_hisens.seg ├── Tumor1.Normal1_purity.rds ├── Tumor1.Normal1_purity.seg ├── Tumor1.Normal1.qc.txt ├── Tumor1.Normal1.snp_pileup.gz ├── Tumor1.Normal1.txt ├── Tumor2.Normal2.arm_level.txt ├── Tumor2.Normal2.gene_level.txt ├── Tumor2.Normal2_hisens.ccf.maf ├── Tumor2.Normal2_hisens.rds ├── Tumor2.Normal2_hisens.seg ├── Tumor2.Normal2_purity.rds ├── Tumor2.Normal2_purity.seg ├── Tumor2.Normal2.qc.txt ├── Tumor2.Normal2.snp_pileup.gz ├── Tumor2.Normal2.txt └── logs ├── success └── failed |
https://github.com/mskcc/pluto-cwl.git
Path: cwl/facets-workflow.cwl Branch/Commit ID: 462f6015c9268a4205b6e81de018a470b8a4a153 |
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Generate ATDP heatmap using Homer
Generate ATDP heatmap centered on TSS from an array of input BAM files and genelist TSV file. Returns array of heatmap JSON files with the names that have the same basenames as input BAM files, but with .json extension |
https://github.com/datirium/workflows.git
Path: workflows/heatmap.cwl Branch/Commit ID: dda9e6e06a656b7b3fa7504156474b962fe3953c |
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Subworkflow to allow calling cnvkit with cram instead of bam files
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https://github.com/genome/analysis-workflows.git
Path: definitions/subworkflows/cram_to_cnvkit.cwl Branch/Commit ID: 5cb188131f786ed33156e2f0e3dd63ab9c04245d |
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Deprecated. RNA-Seq pipeline single-read
The original [BioWardrobe's](https://biowardrobe.com) [PubMed ID:26248465](https://www.ncbi.nlm.nih.gov/pubmed/26248465) **RNA-Seq** basic analysis for a **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.cwl Branch/Commit ID: 261c0232a7a40880f2480b811ed2d7e89c463869 |
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umi duplex alignment fastq workflow
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https://github.com/genome/analysis-workflows.git
Path: definitions/pipelines/alignment_umi_duplex.cwl Branch/Commit ID: 3bebaf9b70331de9f4845e2223c55082f5a812fb |
