Explore Workflows

https://doi.org/10.1007/s12275-011-1213-z

https://github.com/ProteinsWebTeam/ebi-metagenomics-cwl.git

Path: workflows/rna-selector.cwl

Branch/Commit ID: ca6ca613

https://github.com/Marco-Salvi/dtc51.git

Path: ST520101.cwl

Branch/Commit ID: main

https://github.com/ProteinsWebTeam/ebi-metagenomics-cwl.git

Path: workflows/emg-pipeline-v3-paired.cwl

Branch/Commit ID: master

somatic_exome is designed to perform processing of mutant/wildtype H.sapiens exome sequencing data. It features BQSR corrected alignments, 4 caller variant detection, and vep style annotations. Structural variants are detected via manta and cnvkit. In addition QC metrics are run, including somalier concordance metrics. example input file = analysis_workflows/example_data/somatic_exome.yaml

https://github.com/apaul7/cancer-genomics-workflow.git

Path: definitions/pipelines/somatic_exome.cwl

Branch/Commit ID: low-vaf

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_sv.txt ├── data_fusions.txt ├── data_mutations_extended.txt ├── meta_clinical_patient.txt ├── meta_clinical_sample.txt ├── meta_CNA.txt ├── meta_sv.txt ├── meta_fusions.txt ├── meta_mutations_extended.txt ├── meta_study.txt ├── <project_id>_data_cna_hg19.seg └── <project_id>_meta_cna_hg19_seg.txt

https://github.com/mskcc/pluto-cwl.git

Path: cwl/workflow_with_facets.cwl

Branch/Commit ID: master

https://github.com/johnbradley/imads-worker.git

Path: predict_service/preference-workflow.cwl

Branch/Commit ID: master

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

Path: task_types/tt_kmer_build_tree.cwl

Branch/Commit ID: test

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

Path: definitions/subworkflows/sequence_to_bqsr_nonhuman.cwl

Branch/Commit ID: master

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

Path: v1.0/v1.0/output-arrays-file-wf.cwl

Branch/Commit ID: master

https://github.com/fgomez02/analysis-workflows.git

Path: definitions/subworkflows/qc_wgs.cwl

Branch/Commit ID: No_filters_detect_variants