HapBoost: A fast approach to boosting haplotype association analyses in genome-wide association studies

Xiang Wan, Can Yang, Qiang Yang, Hongyu Zhao, Weichuan Yu

Research output: Contribution to journalJournal articlepeer-review

2 Citations (Scopus)

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.

Original languageEnglish
Article number6419694
Pages (from-to)207-212
Number of pages6
JournalIEEE/ACM Transactions on Computational Biology and Bioinformatics
Volume10
Issue number1
DOIs
Publication statusPublished - Jan 2013

Scopus Subject Areas

  • Biotechnology
  • Genetics
  • Applied Mathematics

User-Defined Keywords

  • genome-wide association studies
  • haplotype
  • linkage disequilibrium
  • SNP

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