Explore Workflows
View already parsed workflows here or click here to add your own
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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. |
https://github.com/datirium/workflows.git
Path: workflows/pca.cwl Branch/Commit ID: 09267e79fd867aa68a219c69e6db7d8e2e877be2 |
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hmmsearch_wnode and gpx_qdump combined workflow to apply scatter/gather
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https://github.com/ncbi/pgap.git
Path: task_types/tt_hmmsearch_wnode_plus_qdump.cwl Branch/Commit ID: d218e081d8f6a4fdab56a38ce0fc2fae6216cecc |
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Build STAR indices
Workflow runs [STAR](https://github.com/alexdobin/STAR) v2.5.3a (03/17/2017) PMID: [23104886](https://www.ncbi.nlm.nih.gov/pubmed/23104886) to build indices for reference genome provided in a single FASTA file as fasta_file input and GTF annotation file from annotation_gtf_file input. Generated indices are saved in a folder with the name that corresponds to the input genome. |
https://github.com/datirium/workflows.git
Path: workflows/star-index.cwl Branch/Commit ID: a839eb6390974089e1a558c49fc07b4c66c50767 |
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align_sort_sa
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https://github.com/ncbi/pgap.git
Path: task_types/tt_align_sort_sa.cwl Branch/Commit ID: d218e081d8f6a4fdab56a38ce0fc2fae6216cecc |
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Build STAR indices
Workflow runs [STAR](https://github.com/alexdobin/STAR) v2.5.3a (03/17/2017) PMID: [23104886](https://www.ncbi.nlm.nih.gov/pubmed/23104886) to build indices for reference genome provided in a single FASTA file as fasta_file input and GTF annotation file from annotation_gtf_file input. Generated indices are saved in a folder with the name that corresponds to the input genome. |
https://github.com/datirium/workflows.git
Path: workflows/star-index.cwl Branch/Commit ID: 2f0db4b3c515f91c5cfda19c78cf90d339390986 |
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final_filtering
Final filtering |
https://gitlab.bsc.es/lrodrig1/structuralvariants_poc.git
Path: structuralvariants/cwl/subworkflows/final_filtering.cwl Branch/Commit ID: f248ac3ccbf6840af721251c7e9451abd9b2c09f |
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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 |
https://github.com/datirium/workflows.git
Path: workflows/rnaseq-se.cwl Branch/Commit ID: a409db2289b86779897ff19003bd351701a81c50 |
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Trim Galore RNA-Seq pipeline single-read strand specific
Note: should be updated 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-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 file 2. Use STAR to align reads from input FASTQ file according to the predefined reference indices; generate unsorted BAM file and alignment statistics file 3. Use fastx_quality_stats to analyze input FASTQ file and generate quality statistics file 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 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 |
https://github.com/datirium/workflows.git
Path: workflows/trim-rnaseq-se-dutp.cwl Branch/Commit ID: a839eb6390974089e1a558c49fc07b4c66c50767 |
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Single-cell Multiome ATAC and RNA-Seq Alignment
Single-cell Multiome ATAC and RNA-Seq Alignment ==================================================================== Runs Cell Ranger ARC Count to quantifies chromatin accessibility and gene expression from a single-cell Multiome ATAC and RNA-Seq library |
https://github.com/Barski-lab/scRNA-Seq-Analysis.git
Path: workflows/sc-multiome-align-wf.cwl Branch/Commit ID: 280cad66c2a5b2e1b66e4f8a5469942e88df5b74 |
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SoupX - an R package for the estimation and removal of cell free mRNA contamination
Devel version of Single-Cell Advanced Cell Ranger Pipeline (SoupX) ================================================================= |
https://github.com/datirium/workflows.git
Path: workflows/soupx.cwl Branch/Commit ID: a839eb6390974089e1a558c49fc07b4c66c50767 |
