Fastanova: an efficient algorithm for genome-wide association study

Studying the association between quantitative phenotype (such as height or weight) and single nucleotide polymorphisms (SNPs) is an important problem in biology. To understand underlying mechanisms of complex phenotypes, it is often necessary to consider joint genetic effects across multiple SNPs. ANOVA (analysis of variance) test is routinely used in association study. Important findings from studying gene-gene (SNP-pair) interactions are appearing in the literature. However, the number of SNPs can be up to millions. Evaluating joint effects of SNPs is a challenging task even for SNPpairs. Moreover, with large number of SNPs correlated, permutation procedure is preferred over simple Bonferroni correction for properly controlling family-wise error rate and retaining mapping power, which dramatically increases the computational cost of association study. In this paper, we study the problem of finding SNP-pairs that have significant associations with a given quantitative phenotype. We p...

• Type: Conference
• Year: 2008
• Where: KDD
• Authors: Xiang Zhang, Fei Zou, Wei Wang 0010
• Keywords: ANOVA Test, Data Mining, KDD 2008, Single-snp Anova Test, SNP-pair ANOVA Test