title: HapBoost: a fast approach to boosting haplotype association analyses in genome-wide association studies.
abstract: Genome-wide association study (GWAS) has been successful in identifying genetic variants that are associated with complex human diseases. In GWAS, multilocus association analyses through linkage disequilibrium (LD), named haplotype-based analyses, may have greater power than single-locus analyses for detecting disease susceptibility loci. However, the large number of SNPs genotyped in GWAS poses great computational challenges in the detection of haplotype associations. We present a fast method named HapBoost for finding haplotype associations, which can be applied to quickly screen the whole genome. The effectiveness of HapBoost is demonstrated by using both synthetic and real data sets. The experimental results show that the proposed approach can achieve comparably accurate results while it performs much faster than existing methods.
authors.affiliation: Department of Computer Science and Institute of Computational and Theoretical Studies, Hong Kong Baptist University, Hong Kong. eexiangw@ust.hk
authors.forename: Xiang
authors.initials: X
authors.lastname: Wan
authors.forename: Can
authors.initials: C
authors.lastname: Yang
authors.forename: Qiang
authors.initials: Q
authors.lastname: Yang
authors.forename: Hongyu
authors.initials: H
authors.lastname: Zhao
authors.forename: Weichuan
authors.initials: W
authors.lastname: Yu
mesh_terms: D016000:Cluster Analysis; D019295:Computational Biology / Q000379:methods*; D030541:Databases, Genetic; D004194:Disease / Q000235:genetics; D015894:Genome, Human; D055106:Genome-Wide Association Study / Q000379:methods*; D006239:Haplotypes; D006801:Humans; D015810:Linkage Disequilibrium; D008390:Markov Chains; D020641:Polymorphism, Single Nucleotide; D012372:ROC Curve; D012984:Software