Explore Workflows
View already parsed workflows here or click here to add your own
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count-lines4-wf.cwl
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![]() Path: cwltool/schemas/v1.0/v1.0/count-lines4-wf.cwl Branch/Commit ID: e9c83739a93fa0b18f8dea2f98b632a9e32725c9 |
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trim-rnaseq-pe.cwl
Runs RNA-Seq BioWardrobe basic analysis with pair-end data file. |
![]() Path: workflows/trim-rnaseq-pe.cwl Branch/Commit ID: ea2a2ab57710fcf067f67305f3dd6ad29094da1a |
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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. |
![]() Path: workflows/pca.cwl Branch/Commit ID: e238d1756f1db35571e84d72e1699e5d1540f10c |
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count-lines11-null-step-wf.cwl
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![]() Path: tests/count-lines11-null-step-wf.cwl Branch/Commit ID: c7c97715b400ff2194aa29fc211d3401cea3a9bf |
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RNA-Seq pipeline single-read
The original [BioWardrobe's](https://biowardrobe.com) [PubMed ID:26248465](https://www.ncbi.nlm.nih.gov/pubmed/26248465) **RNA-Seq** basic analysis for a **single-read** 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-read RNA-Seq data. It performs the following steps: 1. Use STAR to align reads from input FASTQ file according to the predefined reference indices; generate unsorted BAM file and alignment statistics file 2. Use fastx_quality_stats to analyze input FASTQ file and generate quality statistics file 3. 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 file 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 |
![]() Path: workflows/rnaseq-se.cwl Branch/Commit ID: 730b40bc403263b724399a952c0f3e2d28f13519 |
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cond-wf-005.1.cwl
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![]() Path: testdata/cond-wf-005.1.cwl Branch/Commit ID: 0ad6983898f0d9001fe0f416f97c4d8b940e384a |
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Motif Finding with HOMER with custom background regions
Motif Finding with HOMER with custom background regions --------------------------------------------------- HOMER contains a novel motif discovery algorithm that was designed for regulatory element analysis in genomics applications (DNA only, no protein). It is a differential motif discovery algorithm, which means that it takes two sets of sequences and tries to identify the regulatory elements that are specifically enriched in on set relative to the other. It uses ZOOPS scoring (zero or one occurrence per sequence) coupled with the hypergeometric enrichment calculations (or binomial) to determine motif enrichment. HOMER also tries its best to account for sequenced bias in the dataset. It was designed with ChIP-Seq and promoter analysis in mind, but can be applied to pretty much any nucleic acids motif finding problem. For more information please refer to: ------------------------------------- [Official documentation](http://homer.ucsd.edu/homer/motif/) |
![]() Path: workflows/homer-motif-analysis-bg.cwl Branch/Commit ID: 7ced5a5259dbd8b3fc64456beaeffd44f4a24081 |
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step-valuefrom3-wf_v1_1.cwl
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![]() Path: testdata/step-valuefrom3-wf_v1_1.cwl Branch/Commit ID: 0ab1d42d10f7311bb4032956c4a6f3d2730d9507 |
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tt_blastn_wnode
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![]() Path: task_types/tt_blastn_wnode.cwl Branch/Commit ID: e3f18c61d1bbf65e40921dbd044369da4523ee3e |
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io-int-default-tool-and-wf.cwl
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![]() Path: tests/io-int-default-tool-and-wf.cwl Branch/Commit ID: c7c97715b400ff2194aa29fc211d3401cea3a9bf |