Explore Workflows

View already parsed workflows here or click here to add your own

Graph Name Retrieved From View
workflow graph js-expr-req-wf.cwl#wf

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

Path: cwltool/schemas/v1.0/v1.0/js-expr-req-wf.cwl

Branch/Commit ID: 3ed10d0ea7ac57550433a89a92bdbe756bdb0e40

Packed ID: wf
workflow graph io-file-default-wf.cwl

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

Path: v1.0/v1.0/io-file-default-wf.cwl

Branch/Commit ID: master
workflow graph GRO_run.cwl

https://github.com/JFRudzinski/CWL_example.git

Path: test_workflow_notables_clean/workflow/GRO_run.cwl

Branch/Commit ID: master
workflow graph PCA - Principal Component Analysis

Principal Component Analysis --------------- Principal component analysis (PCA) is a statistical procedure that uses an orthogonal transformation to convert a set of observations of possibly correlated variables (entities each of which takes on various numerical values) into a set of values of linearly uncorrelated variables called principal components. The calculation is done by a singular value decomposition of the (centered and possibly scaled) data matrix, not by using eigen on the covariance matrix. This is generally the preferred method for numerical accuracy.

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

Path: workflows/pca.cwl

Branch/Commit ID: master
workflow graph upload_results_workflow.cwl

https://github.com/nci-gdc/htseq-cwl.git

Path: workflows/subworkflows/upload_results_workflow.cwl

Branch/Commit ID: master
workflow graph transform.cwl

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

Path: workflows/dnaseq/transform.cwl

Branch/Commit ID: 1.1
workflow graph downsample unaligned BAM and align

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

Path: definitions/subworkflows/downsampled_alignment.cwl

Branch/Commit ID: downsample_and_recall
workflow graph Trim Galore RNA-Seq pipeline paired-end

The 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 must be used with paired-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 2 (after running STAR) 5. Generate BigWig file using 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.cwl

Branch/Commit ID: master
workflow graph exome alignment with qc, no bqsr, no verify_bam_id

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

Path: definitions/pipelines/alignment_exome_nonhuman.cwl

Branch/Commit ID: master
workflow graph import_schema-def.cwl

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

Path: v1.0/v1.0/import_schema-def.cwl

Branch/Commit ID: master