EXtasy: Variant Prioritization by Genomic Data Fusion

Overview

Journal Nat Methods

Specialties Biomedical Engineering
Pathology

Date 2013 Oct 1

PMID 24076761

Citations 98

Authors

Alejandro Sifrim

Dusan Popovic

Leon-Charles Tranchevent

Amin ArdeshirDavani

Ryo Sakai

Peter Konings

Joris R Vermeesch

Jan Aerts

Bart De Moor

Yves Moreau

Affiliations

Soon will be listed here.

Abstract

Massively parallel sequencing greatly facilitates the discovery of novel disease genes causing Mendelian and oligogenic disorders. However, many mutations are present in any individual genome, and identifying which ones are disease causing remains a largely open problem. We introduce eXtasy, an approach to prioritize nonsynonymous single-nucleotide variants (nSNVs) that substantially improves prediction of disease-causing variants in exome sequencing data by integrating variant impact prediction, haploinsufficiency prediction and phenotype-specific gene prioritization.

Citing Articles

Yves Moreau has received the 2023 Einstein Foundation Individual Award for Promoting Quality in Research.

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