TY - JOUR AB - Methods to interpret personal genome sequences are increasingly required. Here, we report a novel framework (EvoTol) to identify disease-causing genes using patient sequence data from within protein coding-regions. EvoTol quantifies a gene's intolerance to mutation using evolutionary conservation of protein sequences and can incorporate tissue-specific gene expression data. We apply this framework to the analysis of whole-exome sequence data in epilepsy and congenital heart disease, and demonstrate EvoTol's ability to identify known disease-causing genes is unmatched by competing methods. Application of EvoTol to the human interactome revealed networks enriched for genes intolerant to protein sequence variation, informing novel polygenic contributions to human disease. AU - Rackham,OJL AU - Shihab,HA AU - Johnson,MR AU - Petretto,E DO - nar/gku1322 PY - 2014/// SN - 0305-1048 TI - EvoTol: a protein-sequence based evolutionary intolerance framework for disease-gene prioritization T2 - Nucleic Acids Research UR - http://dx.doi.org/10.1093/nar/gku1322 UR - http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000352487100006&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202 UR - http://hdl.handle.net/10044/1/57229 VL - 43 ER -