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

Erdem Türk, Akif Ayaz, Ayhan Yüksek, Barış E Süzek

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Article in PeerJ, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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4 · The record

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5 · Who and what money

Authors and funding

4 authors at 2 institutions in 1 country.

Erdem TürkDepartment of Computer Engineering, Muğla Sıtkı Koçman University, Muğla, Turkey.

Akif AyazDepartment of Medical Genetics, School of Medicine, İstanbul Medipol University, İstanbul, Turkey.

Ayhan YüksekDepartment of Computer Engineering, Muğla Sıtkı Koçman University, Muğla, Turkey.

Barış E SüzekDepartment of Computer Engineering, Muğla Sıtkı Koçman University, Muğla, Turkey.

Muğla University · TRIstanbul Medipol University · TR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

ExistentialismHirschsprung DiseaseDatabases, FactualExome SequencingGenomicsHumansClinical NGS informaticsGenetic diseasesGenetic disposition to diseaseGenetic variantsMedical geneticsNext-generation sequence (NGS) analysisWhole-exome sequencing (WES) analysis

Identifiers

PMID37727687

DOI10.7717/peerj.16026

PMCPMC10506587

OpenAlexW4386783705

What OpenQuestion holds

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LicenceCC BY

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.