HapBoost: A Fast Approach to Boosting Haplotype Association Analyses in Genome-Wide Association Studies
Issue No. 01 - Jan.-Feb. (2013 vol. 10)
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/TCBB.2013.6
Xiang Wan , Dept. of Comput. Sci., Hong Kong Baptist Univ., Hong Kong, China
Can Yang , Div. of Biostat., Yale Univ., New Haven, CT, USA
Qiang Yang , Dept. of Comput. Sci. & Eng., Hong Kong Univ. of Sci. & Technol., Hong Kong, China
Hongyu Zhao , Div. of Biostat., Yale Univ., New Haven, CT, USA
Weichuan Yu , Dept. of Electron. & Comput. Eng., Hong Kong Univ. of Sci. & Technol., Hong Kong, China
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.
Bioinformatics, Genomics, Diseases, Estimation, Testing, Computational biology, Educational institutions
Xiang Wan, Can Yang, Qiang Yang, Hongyu Zhao and Weichuan Yu, "HapBoost: A Fast Approach to Boosting Haplotype Association Analyses in Genome-Wide Association Studies," in IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol. 10, no. 1, pp. 207-212, 2013.