Explore Workflows

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Graph Name Retrieved From View
workflow graph scatter-wf2_v1_0.cwl

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

Path: testdata/scatter-wf2_v1_0.cwl

Branch/Commit ID: 77669d4dd1d1ebd2bdd9810f911608146d9b8e51
workflow graph umi molecular alignment workflow

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

Path: definitions/subworkflows/molecular_alignment.cwl

Branch/Commit ID: 49508a2757ff2f49f1c200774a38af1c12b531bf
workflow graph Subworkflow to allow calling cnvkit with cram instead of bam files

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

Path: definitions/subworkflows/cram_to_cnvkit.cwl

Branch/Commit ID: 2979b565f88ceebca934611adbf3fb8cefd65a19
workflow graph RNA-seq alelle specific pipeline for single-read data

Allele specific RNA-Seq single-read workflow

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

Path: workflows/allele-rnaseq-se.cwl

Branch/Commit ID: c602e3cdd72ff904dd54d46ba2b5146eb1c57022
workflow graph scRNA-seq pipeline using Salmon and Alevin

https://github.com/hubmapconsortium/salmon-rnaseq.git

Path: pipeline.cwl

Branch/Commit ID: 8af5a1c9c99b06e7024e4ddbf45a15cf07ea9410
workflow graph 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

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

Path: cwl/workflow_with_facets.cwl

Branch/Commit ID: 342e6f1f4f7a3839e579fbe96ccc8d6f7a61ac77
workflow graph Trim Galore SMARTer RNA-Seq pipeline paired-end strand specific

https://chipster.csc.fi/manual/library-type-summary.html 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

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

Path: workflows/trim-rnaseq-pe-smarter-dutp.cwl

Branch/Commit ID: aebf2355539fdf81fd9082616f8b21440d2691c6
workflow graph Cellranger aggr - aggregates data from multiple Cellranger runs

Devel version of Single-Cell Cell Ranger Aggregate ================================================== Workflow calls \"cellranger aggr\" command to combine output files from \"cellranger count\" (the molecule_info.h5 file from each run) into a single feature-barcode matrix containing all the data. When combining multiple GEM wells, the barcode sequences for each channel are distinguished by a GEM well suffix appended to the barcode sequence. Each GEM well is a physically distinct set of GEM partitions, but draws barcode sequences randomly from the pool of valid barcodes, known as the barcode whitelist. To keep the barcodes unique when aggregating multiple libraries, we append a small integer identifying the GEM well to the barcode nucleotide sequence, and use that nucleotide sequence plus ID as the unique identifier in the feature-barcode matrix. For example, AGACCATTGAGACTTA-1 and AGACCATTGAGACTTA-2 are distinct cell barcodes from different GEM wells, despite having the same barcode nucleotide sequence. This number, which tells us which GEM well this barcode sequence came from, is called the GEM well suffix. The numbering of the GEM wells will reflect the order that the GEM wells were provided in the \"molecule_info_h5\" and \"gem_well_labels\" inputs. When combining data from multiple GEM wells, the \"cellranger aggr\" pipeline automatically equalizes the average read depth per cell between groups before merging. This approach avoids artifacts that may be introduced due to differences in sequencing depth. It is possible to turn off normalization or change the way normalization is done through the \"normalization_mode\" input. The \"none\" value may be appropriate if you want to maximize sensitivity and plan to deal with depth normalization in a downstream step.

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

Path: workflows/cellranger-aggr.cwl

Branch/Commit ID: 57437c1e9f881411b65f79acd64b7cf14df5b901
workflow graph paramref_arguments_self.cwl

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

Path: tests/wf/paramref_arguments_self.cwl

Branch/Commit ID: e1a9100dff381ebd59b2a74806f705b7c68a8584
workflow graph rnaseq-se-dutp.cwl

RNA-Seq basic analysis workflow for strand specific single-read experiment.

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

Path: workflows/rnaseq-se-dutp.cwl

Branch/Commit ID: e284e3f6dff25037b209895c52f2abd37a1ce1bf