An entropy-based measure for QTL mapping using extreme samples of population.

Quantitative trait locus (QTL) mapping can be accomplished through the method of selective genotyping, which is based on the differences of frequencies between an upper sample and a lower sample in population. However, amplifying the differences in marker allele frequencies in extreme samples may increase the probability for QTL mapping. Shannon entropy, which is a nonlinear function of allele frequencies, can be used to amplify the differences in marker allele frequencies. In this paper, we present a novel measure for linkage disequilibrium (LD) between a marker and single QTL, that is based on the comparison of the entropy and conditional entropy in a marker in extreme samples of population. This measure of LD between the marker and the trait locus can be used when the marker allele frequencies are known in the extreme samples of a population. We investigate the mapping performance in both analytic and simulation scenarios of a single QTL linked to a single marker. Our results show that the measure has very reasonable performance. In addition, a simulation study is performed on the basis of the haplotype frequencies of 10 SNPs of angiotensin-I converting enzyme (ACE) genes.