DEVOUR
DEVOUR identifies low-coverage regions in whole-exome sequencing (WES) read alignments and annotates known variants within those regions to reveal clinically relevant deleterious variants missed by insufficient read depth.
Key Features:
- Identification of Low-Coverage Regions: Scans WES read alignments to pinpoint genomic intervals with no or low coverage, defined as having a read depth of less than 5.
- Annotation of Known Variants: Annotates known variants within identified low-coverage regions using clinical variant annotation databases.
- Clinical Relevance: Detects deleterious variants in uncovered regions and associates them with patient clinical phenotypes to support diagnostic interpretation.
Scientific Applications:
- Hirschsprung disease WES analysis (NCBI Bioproject PRJEB19327): Identified 98 potential disease-associated variants within low-coverage regions across 28 samples.
Methodology:
Scans WES read alignments to detect genomic regions with insufficient coverage and then annotates those regions using established clinical variant databases.
Topics
Details
- License:
- MIT
- Cost:
- Free of charge
- Tool Type:
- desktop application
- Operating Systems:
- Mac, Linux, Windows
- Programming Languages:
- JavaScript, Python
- Added:
- 4/8/2024
- Last Updated:
- 11/24/2024
Operations
Publications
Türk E, Ayaz A, Yüksek A, Süzek BE. DEVOUR: Deleterious Variants on Uncovered Regions in Whole-Exome Sequencing. PeerJ. 2023;11:e16026. doi:10.7717/peerj.16026. PMID:37727687. PMCID:PMC10506587.
DOI: 10.7717/PEERJ.16026
PMID: 37727687
PMCID: PMC10506587
Funding: - Scientific and Technological Research Council of Turkey: 120E522
Links
Repository
https://github.com/projectDevour/DEVOUR