Explore Workflows
View already parsed workflows here or click here to add your own
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kfdrc_alignment_pipeline.cwl
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Path: dev/pilot-run/worklflows/kfdrc_alignment_pipeline.cwl Branch/Commit ID: e75f0c96153a484db1f882f6ff2a9764519a3179 |
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directory.cwl
Inspect provided directory and return filenames. Generate a new directory and return it (including content). |
Path: tests/wf/directory.cwl Branch/Commit ID: 5bdb3d3dd47d8d1b3a1685220b4b6ce0f94c055e |
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workflow_with_facets.cwl
CWL workflow for generating Roslin / Argos post pipeline analysis files and cBioPortal data and metadata files This workflow includes Facets and Facets Suite usages Inputs ------ The following parameters are required: project_id project_pi request_pi project_short_name project_name project_description cancer_type cancer_study_identifier argos_version_string helix_filter_version is_impact extra_pi_groups pairs The following filenames are required: analysis_mutations_filename analysis_gene_cna_filename analysis_sv_filename analysis_segment_cna_filename cbio_segment_data_filename cbio_meta_cna_segments_filename The following filenames have default values and are optional: cbio_mutation_data_filename cbio_cna_data_filename cbio_fusion_data_filename cbio_clinical_patient_data_filename cbio_clinical_sample_data_filename cbio_clinical_sample_meta_filename cbio_clinical_patient_meta_filename cbio_meta_study_filename cbio_meta_cna_filename cbio_meta_fusions_filename cbio_meta_mutations_filename cbio_cases_all_filename cbio_cases_cnaseq_filename cbio_cases_cna_filename cbio_cases_sequenced_filename Output ------ Workflow output should look like this: output ├── analysis │ ├── <project_id>.gene.cna.txt │ ├── <project_id>.muts.maf │ ├── <project_id>.seg.cna.txt │ └── <project_id>.svs.maf ├── facets │ ├── <tumor_id>.<normal_id> (passed) │ │ └── <facets_files> │ └── <tumor_id>.<normal_id> (failed) │ └── <log_files> └── portal ├── case_list │ ├── cases_all.txt │ ├── cases_cnaseq.txt │ ├── cases_cna.txt │ └── cases_sequenced.txt ├── data_clinical_patient.txt ├── data_clinical_sample.txt ├── data_CNA.ascna.txt ├── data_CNA.scna.txt ├── data_CNA.txt ├── data_fusions.txt ├── data_mutations_extended.txt ├── meta_clinical_patient.txt ├── meta_clinical_sample.txt ├── meta_CNA.txt ├── meta_fusions.txt ├── meta_mutations_extended.txt ├── meta_study.txt ├── <project_id>_data_cna_hg19.seg └── <project_id>_meta_cna_hg19_seg.txt |
Path: cwl/workflow_with_facets.cwl Branch/Commit ID: 462f6015c9268a4205b6e81de018a470b8a4a153 |
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scatter-wf1_v1_0.cwl
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Path: testdata/scatter-wf1_v1_0.cwl Branch/Commit ID: e949503ac0dd7e22ba9b04ac51926d13780f9cee |
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fail-wf.cwl
Run failtool which will fail |
Path: input-data/fail-wf.cwl Branch/Commit ID: ceb1c2731dd4c3c20229a5cad06a64a487103c21 |
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chipseq-pe.cwl
Runs ChIP-Seq BioWardrobe basic analysis with paired-end input data files. |
Path: workflows/chipseq-pe.cwl Branch/Commit ID: 9a03dbe8829ca649814d9c8bd11fe3a673750a95 |
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Cell Ranger Aggregate (RNA, RNA+VDJ)
Cell Ranger Aggregate (RNA, RNA+VDJ) Combines outputs from multiple runs of either “Cell Ranger Count (RNA)” or “Cell Ranger Count (RNA+VDJ)” pipelines. The results of this workflow are primarily used in “Single-Cell RNA-Seq Filtering Analysis” and “Single-Cell Immune Profiling Analysis” pipelines. |
Path: workflows/cellranger-aggr.cwl Branch/Commit ID: b4d578c2ba4713a5a22163d9f8c7105acda1f22e |
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Trim Galore RNA-Seq pipeline paired-end strand specific
Modified original [BioWardrobe's](https://biowardrobe.com) [PubMed ID:26248465](https://www.ncbi.nlm.nih.gov/pubmed/26248465) **RNA-Seq** basic analysis for a **pair-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 single-end RNA-Seq data. It performs the following steps: 1. Trim adapters from input FASTQ files 2. Use STAR to align reads from input FASTQ files according to the predefined reference indices; generate unsorted BAM file and alignment statistics file 3. Use fastx_quality_stats to analyze input FASTQ files and generate quality statistics files 4. 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 files 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 |
Path: workflows/trim-rnaseq-pe-dutp.cwl Branch/Commit ID: b4d578c2ba4713a5a22163d9f8c7105acda1f22e |
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Single-Cell RNA-Seq Differential Expression Analysis
Single-Cell RNA-Seq Differential Expression Analysis Identifies differentially expressed genes between any two groups of cells, optionally aggregating gene expression data from single-cell to pseudobulk form. |
Path: workflows/sc-rna-de-pseudobulk.cwl Branch/Commit ID: b4d578c2ba4713a5a22163d9f8c7105acda1f22e |
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step-valuefrom3-wf.cwl
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Path: cwltool/schemas/v1.0/v1.0/step-valuefrom3-wf.cwl Branch/Commit ID: 2ae8117360a3cd4909d9d3f2b35c30bfffb25d0a |
