Explore Workflows
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| Graph | Name | Retrieved From | View |
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Runs InterProScan on batches of sequences to retrieve functional annotations.
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https://github.com/EBI-Metagenomics/workflow-is-cwl.git
Path: workflows/InterProScan-v5-chunked-wf.cwl Branch/Commit ID: 72f702591368397f56d455128f60916902104dd2 |
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Generate genome indices for STAR & bowtie
Creates indices for: * [STAR](https://github.com/alexdobin/STAR) v2.5.3a (03/17/2017) PMID: [23104886](https://www.ncbi.nlm.nih.gov/pubmed/23104886) * [bowtie](http://bowtie-bio.sourceforge.net/tutorial.shtml) v1.2.0 (12/30/2016) It performs the following steps: 1. `STAR --runMode genomeGenerate` to generate indices, based on [FASTA](http://zhanglab.ccmb.med.umich.edu/FASTA/) and [GTF](http://mblab.wustl.edu/GTF2.html) input files, returns results as an array of files 2. Outputs indices as [Direcotry](http://www.commonwl.org/v1.0/CommandLineTool.html#Directory) data type 3. Separates *chrNameLength.txt* file from Directory output 4. `bowtie-build` to generate indices requires genome [FASTA](http://zhanglab.ccmb.med.umich.edu/FASTA/) file as input, returns results as a group of main and secondary files |
https://github.com/datirium/workflows.git
Path: workflows/genome-indices.cwl Branch/Commit ID: 44214a9d02e6d85b03eb708552ed812ae3d4a733 |
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downsample unaligned BAM and align
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https://github.com/genome/analysis-workflows.git
Path: definitions/subworkflows/downsampled_alignment.cwl Branch/Commit ID: ae75b938e6e8ae777a55686bbacad824b3c6788c |
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oxog_sub_wf.cwl
This is a subworkflow of the main oxog_varbam_annotat_wf workflow - this is not meant to be run as a stand-alone workflow! |
https://github.com/david4096/oxog-dockstore-tools.git
Path: oxog_sub_wf.cwl Branch/Commit ID: 6366ed398da10019b6d81a789291af6d909f28f4 |
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taxonomy_check_16S
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https://github.com/ncbi/pgap.git
Path: task_types/tt_taxonomy_check_16S.cwl Branch/Commit ID: f5d70f3ad365a2c017fab1c9654c88bc1caf41aa |
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gathered exome alignment and somatic variant detection
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https://github.com/genome/analysis-workflows.git
Path: definitions/pipelines/somatic_exome_gathered.cwl Branch/Commit ID: 061d3a2fbcd8a1c39c0b38c549e528deb24a9d54 |
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RNA-Seq pipeline paired-end strand specific
The original [BioWardrobe's](https://biowardrobe.com) [PubMed ID:26248465](https://www.ncbi.nlm.nih.gov/pubmed/26248465) **RNA-Seq** basic analysis for a **paired-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 paired-end RNA-Seq data. It performs the following steps: 1. Use STAR to align reads from input FASTQ files according to the predefined reference indices; generate unsorted BAM file and alignment statistics file 2. Use fastx_quality_stats to analyze input FASTQ files and generate quality statistics files 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) 4. Generate BigWig file on the base of sorted BAM file 5. Map input FASTQ files to predefined rRNA reference indices using Bowtie to define the level of rRNA contamination; export resulted statistics to file 6. 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-pe-dutp.cwl Branch/Commit ID: d1bef74924efcb8bfaa00987b3f148d5a192b7a9 |
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Motif Finding with HOMER with target and background regions from peaks
Motif Finding with HOMER with target and background regions from peaks --------------------------------------------------- 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/) |
https://github.com/datirium/workflows.git
Path: workflows/homer-motif-analysis-peak.cwl Branch/Commit ID: a1f6ca50fcb0881781b3ba0306dd61ebf555eaba |
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group-isoforms-batch.cwl
Workflow runs group-isoforms.cwl tool using scatter for isoforms_file input. genes_filename and common_tss_filename inputs are ignored. |
https://github.com/datirium/workflows.git
Path: tools/group-isoforms-batch.cwl Branch/Commit ID: 4a5c59829ff8b9f3c843e66e3c675dcd9c689ed5 |
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assm_assm_blastn_wnode
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https://github.com/ncbi/pgap.git
Path: task_types/tt_assm_assm_blastn_wnode.cwl Branch/Commit ID: a34f47d1e37af51e387ecdfa5c3047f106c1146b |
