Explore Workflows

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: dda9e6e06a656b7b3fa7504156474b962fe3953c

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

Path: task_types/tt_blastn_wnode.cwl

Branch/Commit ID: 16e3915d2a357e2a861b30911c832e5ddc0c1784

Quality Control and Raw Data trimming

https://gitlab.bsc.es/lrodrig1/structuralvariants_poc.git

Path: structuralvariants/subworkflows/trimmed_fastq.cwl

Branch/Commit ID: 86f2f3fb64e916607637d93cf6715bab90b1f1d3

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

Path: tests/wf/mut2.cwl

Branch/Commit ID: 83038feb2a6fc3bab952e1ecc2a11bfbc8c557b4

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

Path: metadata/indices-header.cwl

Branch/Commit ID: 57863b6131d8262c5ce864adaf8e4038401e71a2

https://github.com/common-workflow-language/cwl-v1.1.git

Path: tests/timelimit3-wf.cwl

Branch/Commit ID: 368b562a1449e8cd39ae8b7f05926b2bfb9b22df

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

Path: testdata/step-valuefrom3-wf_v1_2.cwl

Branch/Commit ID: 77669d4dd1d1ebd2bdd9810f911608146d9b8e51

Workflow runs homer-make-tag-directory.cwl tool using scatter for the following inputs - bam_file - fragment_size - total_reads `dotproduct` is used as a `scatterMethod`, so one element will be taken from each array to construct each job: 1) bam_file[0] fragment_size[0] total_reads[0] 2) bam_file[1] fragment_size[1] total_reads[1] ... N) bam_file[N] fragment_size[N] total_reads[N] `bam_file`, `fragment_size` and `total_reads` arrays should have the identical order.

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

Path: subworkflows/heatmap-prepare.cwl

Branch/Commit ID: 4106b7dc96e968db291b7a61ecd1641aa3b3dd6d

This workflow indexes the input reference FASTA with bwa, and generates faidx and dict file using samtools. This index sample can then be used as input into the germline variant calling workflow, or others that may include this workflow as an upstream source. ### __Inputs__ - FASTA file of the reference genome that will be indexed. ### __Outputs__ - Directory containing the original FASTA, faidx, dict, and bwa index files. - stdout log file (output in Overview tab as well) - stderr log file ### __Data Analysis Steps__ 1. cwl calls dockercontainer robertplayer/scidap-gatk4 to index reference FASTA with bwa, and generates faidx and dict files using samtools ### __References__ - Li, H., & Durbin, R. (2009). Fast and accurate short read alignment with Burrows–Wheeler transform. Bioinformatics, 25(14), 1754–1760.

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

Path: workflows/bwa-index.cwl

Branch/Commit ID: 12e5256de1b680c551c87fd5db6f3bc65428af67

Inspect provided directory and return filenames. Generate a new directory and return it (including content).

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

Path: tests/wf/directory.cwl

Branch/Commit ID: 280a852e74aec08cf79687e8004e17b1ab464534