Explore Workflows

Workflow maps FASTQ files from `fastq_files` input into reference genome `reference_star_indices_folder` and insilico generated `insilico_star_indices_folder` genome (concatenated genome for both `strain1` and `strain2` strains). For both genomes STAR is run with `outFilterMultimapNmax` parameter set to 1 to discard all of the multimapped reads. For insilico genome SAM file is generated. Then it's splitted into two SAM files based on strain names and then sorted by coordinates into the BAM format. For reference genome output BAM file from STAR slignment is also coordinate sorted.

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

Path: subworkflows/allele-alignreads-se-pe.cwl

Branch/Commit ID: 6bf56698c6fe6e781723dea32bc922b91ef49cf3

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

Path: cwltool/schemas/v1.0/v1.0/scatter-wf4.cwl

Branch/Commit ID: cb81b22abc52838823da9945f04d06739ab32fda

Packed ID: main

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

Path: workflows/emg-pipeline-v3.cwl

Branch/Commit ID: 5dc7c5ca618a248a99bd4bf5f3042cdb21947193

1. Convert input SRA file into pair of upsrtream and downstream FASTQ files (run fastq-dump) 2. Analyze quality of FASTQ files (run fastqc with each of the FASTQ files) 3. If any of the following fields in fastqc generated report is marked as failed for at least one of input FASTQ files: \"Per base sequence quality\", \"Per sequence quality scores\", \"Overrepresented sequences\", \"Adapter Content\", - trim adapters (run trimmomatic) 4. Align original or trimmed FASTQ files to reference genome, calculate genes and isoforms expression (run RSEM) 5. Count mapped reads number in sorted BAM file (run bamtools stats) 6. Generate genome coverage BED file (run bedtools genomecov) 7. Sort genearted BED file (run sort) 8. Generate genome coverage bigWig file from BED file (run bedGraphToBigWig)

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

Path: workflows/xenbase-rnaseq-pe.cwl

Branch/Commit ID: 9bf0aa495735f8081bb5870cb32fc898b9e6eb22

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

Path: structuralvariants/cwl/abstract_operations/subworkflows/samtools_view_sam2bam.cwl

Branch/Commit ID: 82e533a98a763a258bd841ed0032c79445478d56

Reverse the lines in a document, then sort those lines.

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

Path: tests/wf/revsort.cwl

Branch/Commit ID: 20d664eff23e59aa57908345bfdb1ceeab3438f2

This workflow remove foreign chromosome comtamination from blastn TSV files

https://github.com/ncbi/cwl-ngs-workflows-cbb.git

Path: workflows/Contamination/fastq-foreign-chromosome-cleanup.cwl

Branch/Commit ID: 11f70a71cb68b3960c2d410ba1fdcd3b8a7e1419

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: 7ae3b75bbe614e59cdeaba06047234a6c40c0fe9

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

Path: tests/wf/nested.cwl

Branch/Commit ID: 20d664eff23e59aa57908345bfdb1ceeab3438f2

https://github.com/EBI-Metagenomics/ebi-metagenomics-cwl.git

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

Branch/Commit ID: ca6ca613f0d3728d9589a6ca6293e66dfde87bfb