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 language | English |
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Article number | 6419694 |
Pages (from-to) | 207-212 |
Number of pages | 6 |
Journal | IEEE/ACM Transactions on Computational Biology and Bioinformatics |
Volume | 10 |
Issue number | 1 |
DOIs | |
Publication status | Published - Jan 2013 |
Scopus Subject Areas
- Biotechnology
- Genetics
- Applied Mathematics
User-Defined Keywords
- genome-wide association studies
- haplotype
- linkage disequilibrium
- SNP