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Network‐Informed Gene Ranking Tackles Genetic Heterogeneity in Exome‐Sequencing Studies of Monogenic Disease
Author(s) -
Dand Nick,
Schulz Reiner,
Weale Michael E.,
Southgate Laura,
Oakey Rebecca J.,
Simpson Michael A.,
Schlitt Thomas
Publication year - 2015
Publication title -
human mutation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.981
H-Index - 162
eISSN - 1098-1004
pISSN - 1059-7794
DOI - 10.1002/humu.22906
Subject(s) - exome sequencing , biology , exome , genetic heterogeneity , genetics , gene , computational biology , disease , identification (biology) , dna sequencing , candidate gene , mutation , phenotype , medicine , botany , pathology
Genetic heterogeneity presents a significant challenge for the identification of monogenic disease genes. Whole-exome sequencing generates a large number of candidate disease-causing variants and typical analyses rely on deleterious variants being observed in the same gene across several unrelated affected individuals. This is less likely to occur for genetically heterogeneous diseases, making more advanced analysis methods necessary. To address this need, we present HetRank, a flexible gene-ranking method that incorporates interaction network data. We first show that different genes underlying the same monogenic disease are frequently connected in protein interaction networks. This motivates the central premise of HetRank: those genes carrying potentially pathogenic variants and whose network neighbors do so in other affected individuals are strong candidates for follow-up study. By simulating 1,000 exome sequencing studies (20,000 exomes in total), we model varying degrees of genetic heterogeneity and show that HetRank consistently prioritizes more disease-causing genes than existing analysis methods. We also demonstrate a proof-of-principle application of the method to prioritize genes causing Adams-Oliver syndrome, a genetically heterogeneous rare disease. An implementation of HetRank in R is available via the Website http://sourceforge.net/p/hetrank/.