Explore Workflows

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Graph Name Retrieved From View
workflow graph collate_unique_rRNA_headers.cwl

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

Path: tools/collate_unique_rRNA_headers.cwl

Branch/Commit ID: ef3c7b2
workflow graph RNASelector as a CWL workflow

https://doi.org/10.1007/s12275-011-1213-z

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

Path: workflows/rna-selector.cwl

Branch/Commit ID: ca6ca613
workflow graph Trim Galore RNA-Seq pipeline paired-end

The original [BioWardrobe's](https://biowardrobe.com) [PubMed ID:26248465](https://www.ncbi.nlm.nih.gov/pubmed/26248465) **RNA-Seq** basic analysis for a **pair-end** experiment. A corresponded input [FASTQ](http://maq.sourceforge.net/fastq.shtml) file has to be provided. Current workflow must be used with paired-end RNA-Seq data. It performs the following steps: 1. Trim adapters from input FASTQ files 2. Use STAR to align reads from input FASTQ files according to the predefined reference indices; generate unsorted BAM file and alignment statistics file 3. Use fastx_quality_stats to analyze input FASTQ files and generate quality statistics files 4. Use samtools sort to generate coordinate sorted BAM(+BAI) file pair from the unsorted BAM file obtained on the step 2 (after running STAR) 5. Generate BigWig file using sorted BAM file 6. Map input FASTQ files 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-pe.cwl

Branch/Commit ID: b4d578c2ba4713a5a22163d9f8c7105acda1f22e
workflow graph foreign_screening.cwl

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

Path: vecscreen/foreign_screening.cwl

Branch/Commit ID: test
workflow graph trimmed_fastq

Quality Control (raw data), Raw Data trimming and Quality Control (pre-processed)

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

Path: structuralvariants/cwl/subworkflows/trimmed_fastq.cwl

Branch/Commit ID: 1.1.3
workflow graph functional analysis prediction with InterProScan

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

Path: workflows/functional_analysis.cwl

Branch/Commit ID: master
workflow graph snpeff_all.cwl

https://github.com/nigyta/rice_reseq.git

Path: workflows/snpeff_all.cwl

Branch/Commit ID: master
workflow graph Long-covid.cwl

https://github.com/cwlviewer-test/Long-covid---aedea650-7a21-11ed-b9d2-e51f21933d80.git

Path: Long-covid---a9e48a70-7a21-11ed-b9d2-e51f21933d80/Long-covid.cwl

Branch/Commit ID: read-potential-cases-disc
workflow graph Get Proteins

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

Path: wf_bacterial_prot_src.cwl

Branch/Commit ID: dev
workflow graph THOR - differential peak calling of ChIP-seq signals with replicates

What is THOR? -------------- THOR is an HMM-based approach to detect and analyze differential peaks in two sets of ChIP-seq data from distinct biological conditions with replicates. THOR performs genomic signal processing, peak calling and p-value calculation in an integrated framework. For more information please refer to: ------------------------------------- Allhoff, M., Sere K., Freitas, J., Zenke, M., Costa, I.G. (2016), Differential Peak Calling of ChIP-seq Signals with Replicates with THOR, Nucleic Acids Research, epub gkw680.

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

Path: workflows/rgt-thor.cwl

Branch/Commit ID: 9b4dc225c537685b9c9a32d931d3892d20953dd7