title: MSEA: detection and quantification of mutation  hotspots through mutation set enrichment analysis.
abstract: Many cancer genes form mutation hotspots that disrupt their functional domains or active sites, leading to gain- or loss-of-function. We propose a mutation set enrichment analysis (MSEA) implemented by two novel methods,MSEA-clust and MSEA-domain, to predict cancer genes based on mutation hotspot patterns. MSEA methods are evaluated by both simulated and real cancer data. We find approximately 51% of the eligible known cancer genes form detectable mutation hotspots. Application of MSEA in eight cancers reveals a total of 82 genes with mutation hotspots,including well-studied cancer genes, known cancer genes re-found in new cancer types, and novel cancer genes.
authors.affiliation: Department of Biomedical Informatics, Vanderbilt University School of Medicine, Nashville, TN 37203, USA.
authors.forename: Peilin
authors.initials: P
authors.lastname: Jia
authors.forename: Quan
authors.initials: Q
authors.lastname: Wang
authors.forename: Qingxia
authors.initials: Q
authors.lastname: Chen
authors.forename: Katherine E
authors.initials: KE
authors.lastname: Hutchinson
authors.forename: William
authors.initials: W
authors.lastname: Pao
authors.forename: Zhongming
authors.initials: Z
authors.lastname: Zhao
mesh_terms: D019295:Computational Biology / Q000379:methods; D003198:Computer Simulation; D004252:DNA Mutational Analysis / Q000379:methods*; D006801:Humans; D009369:Neoplasms / Q000235:genetics*