DEVOUR: Deleterious Variants on Uncovered Regions in Whole-Exome Sequencing.

Clinical NGS informatics Genetic diseases Genetic disposition to disease Genetic variants Medical genetics Next-generation sequence (NGS) analysis Whole-exome sequencing (WES) analysis

Journal

PeerJ
ISSN: 2167-8359
Titre abrégé: PeerJ
Pays: United States
ID NLM: 101603425

Informations de publication

Date de publication:
2023
Historique:
received: 09 05 2023
accepted: 13 08 2023
medline: 21 9 2023
pubmed: 20 9 2023
entrez: 20 9 2023
Statut: epublish

Résumé

The discovery of low-coverage (i.e. uncovered) regions containing clinically significant variants, especially when they are related to the patient's clinical phenotype, is critical for whole-exome sequencing (WES) based clinical diagnosis. Therefore, it is essential to develop tools to identify the existence of clinically important variants in low-coverage regions. Here, we introduce a desktop application, namely DEVOUR (DEleterious Variants On Uncovered Regions), that analyzes read alignments for WES experiments, identifies genomic regions with no or low-coverage (read depth < 5) and then annotates known variants in the low-coverage regions using clinical variant annotation databases. As a proof of concept, DEVOUR was used to analyze a total of 28 samples from a publicly available Hirschsprung disease-related WES project (NCBI Bioproject: https://www.ncbi.nlm.nih.gov/bioproject/?term=PRJEB19327), revealing the potential existence of 98 disease-associated variants in low-coverage regions. DEVOUR is available from https://github.com/projectDevour/DEVOUR under the MIT license.

Identifiants

pubmed: 37727687
doi: 10.7717/peerj.16026
pii: 16026
pmc: PMC10506587
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

e16026

Informations de copyright

©2023 Türk et al.

Déclaration de conflit d'intérêts

The authors declare there are no competing interests.

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Auteurs

Erdem Türk (E)

Department of Computer Engineering, Muğla Sıtkı Koçman University, Muğla, Turkey.
Bioinformatics Graduate Program, Muğla Sıtkı Koçman University, Muğla, Turkey.

Akif Ayaz (A)

Department of Medical Genetics, School of Medicine, İstanbul Medipol University, İstanbul, Turkey.

Ayhan Yüksek (A)

Department of Computer Engineering, Muğla Sıtkı Koçman University, Muğla, Turkey.

Barış E Süzek (BE)

Department of Computer Engineering, Muğla Sıtkı Koçman University, Muğla, Turkey.
Bioinformatics Graduate Program, Muğla Sıtkı Koçman University, Muğla, Turkey.

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