Based On Function Transformation Genome Association Studies

Efficient genotyping methods and the availability of a large collection of singlenucleotide polymorphisms provide valuable tooles for genetic studies of human dis-ease. The standardχ~2 statistic for case-control studies,which use a linear function of probability distribution about allele,has limited power when the number of marker loci is large.We introduce a novel test statistic for genetic association studies that uses a nonlinear function of probability distribution about,allele to amplify the differences in probability distribution of haplotype or allele to maintain statistical power with large numbers of marker loci.Jinying Zhao has investigated the relationship between the entropy-based(a nonlinear function) test statistic and the standardχ~2 statistic and show that,in most cases,the power of the entropy-based test statistic is larger than that of the standardχ~2 statistic.This article is that we use another nonlinear function-mutual information to build a new test statistic:then compare the power of mutual information-based test statistic and that of the entropy-based test statistic and show that,in most cases,the power of the mutual information-based test statistic is larger than that of the entropy-based test statistic.