Explore Workflows

View already parsed workflows here or click here to add your own

Graph Name Retrieved From View
workflow graph Unaligned bam to sorted, markduped bam

https://github.com/genome/analysis-workflows.git

Path: definitions/subworkflows/align_sort_markdup.cwl

Branch/Commit ID: 18600518ce6539a2e29c1707392a4c5da5687fa3
workflow graph kmer_ref_compare_wnode

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

Path: task_types/tt_kmer_ref_compare_wnode.cwl

Branch/Commit ID: 609aead9804a8f31fa9b3dbc7e52105aec487f31
workflow graph tt_univec_wnode.cwl

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

Path: task_types/tt_univec_wnode.cwl

Branch/Commit ID: f1eb0f4eaaf1661044f28d859f7e8d4302525ead
workflow graph biowardrobe_chipseq_se.cwl

The workflow is used to run CHIP-Seq basic analysis with single-end input FASTQ file. In outputs it returns coordinate sorted BAM file alongside with index BAI file, quality statistics of the input FASTQ file, reads coverage in a form of bigWig file, peaks calling data in a form of narrowPeak or broadPeak files.

https://github.com/barski-lab/ga4gh_challenge.git

Path: biowardrobe_chipseq_se.cwl

Branch/Commit ID: f28d47bd0911e5e7210c4dc83f75653a1e0297c9
workflow graph EMG assembly for paired end Illumina

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

Path: workflows/emg-assembly.cwl

Branch/Commit ID: b6d3aaf3fa6695061208c6cdca3d7881cc45400d
workflow graph Trim Galore RNA-Seq pipeline paired-end strand specific

Modified 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 should be used only with the single-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 1 (after running STAR) 5. Generate BigWig file on the base of 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-dutp.cwl

Branch/Commit ID: 581156366f91861bd4dbb5bcb59f67d468b32af3
workflow graph kmer_ref_compare_wnode

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

Path: task_types/tt_kmer_ref_compare_wnode.cwl

Branch/Commit ID: 90a321ecf2d049330bcf0657cc4d764d2c3f42dd
workflow graph 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: 480e99a4bb3046e0565113d9dca294e0895d3b0c
workflow graph kmer_seq_entry_extract_wnode

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

Path: task_types/tt_kmer_seq_entry_extract_wnode.cwl

Branch/Commit ID: 609aead9804a8f31fa9b3dbc7e52105aec487f31
workflow graph kmer_cache_store

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

Path: task_types/tt_kmer_cache_store.cwl

Branch/Commit ID: add6b7724698694e0e72d972e2e85e1ae4e67902