OligoPVP: Phenotype-driven analysis of individual genomic information to prioritize oligogenic disease variants.

Boudellioua, Imane and Kulmanov, Maxat and Schofield, Paul N and Gkoutos, Georgios V and Hoehndorf, Robert (2018) OligoPVP: Phenotype-driven analysis of individual genomic information to prioritize oligogenic disease variants. Scientific reports, 8 (1). p. 14681. ISSN 2045-2322. This article is available to all UHB staff and students via ASK Discovery tool http://tinyurl.com/z795c8c by using their UHB Athens login IDs

[img] Text (PDF file format)
s41598-018-32876-3 - Published Version
Available under License Creative Commons Attribution 4.0.

Download (311kB)
Official URL: https://www.nature.com/articles/s41598-018-32876-3

Abstract

An increasing number of disorders have been identified for which two or more distinct alleles in two or more genes are required to either cause the disease or to significantly modify its onset, severity or phenotype. It is difficult to discover such interactions using existing approaches. The purpose of our work is to develop and evaluate a system that can identify combinations of alleles underlying digenic and oligogenic diseases in individual whole exome or whole genome sequences. Information that links patient phenotypes to databases of gene-phenotype associations observed in clinical or non-human model organism research can provide useful information and improve variant prioritization for genetic diseases. Additional background knowledge about interactions between genes can be utilized to identify sets of variants in different genes in the same individual which may then contribute to the overall disease phenotype. We have developed OligoPVP, an algorithm that can be used to prioritize causative combinations of variants in digenic and oligogenic diseases, using whole exome or whole genome sequences together with patient phenotypes as input. We demonstrate that OligoPVP has significantly improved performance when compared to state of the art pathogenicity detection methods in the case of digenic diseases. Our results show that OligoPVP can efficiently prioritize sets of variants in digenic diseases using a phenotype-driven approach and identify etiologically important variants in whole genomes. OligoPVP naturally extends to oligogenic disease involving interactions between variants in two or more genes. It can be applied to the identification of multiple interacting candidate variants contributing to phenotype, where the action of modifier genes is suspected from pedigree analysis or failure of traditional causative variant identification.

Item Type: Article
Additional Information: This article is available to all UHB staff and students via ASK Discovery tool http://tinyurl.com/z795c8c by using their UHB Athens login IDs
Subjects: QU Biochemistry
QY Clinical pathology
Divisions: Clinical Support > Pathology
Related URLs:
Depositing User: Jamie Edgar
Date Deposited: 20 Dec 2019 13:32
Last Modified: 31 Dec 2019 12:08
URI: http://www.repository.uhblibrary.co.uk/id/eprint/2702

Actions (login required)

View Item View Item