Sampling properties of homozygosity-based statistics for linkage disequilibrium.

Homozygosity-based statistics such as Ohta's identity-in-state (IIS) excess offer the potential to measure linkage disequilibrium for multiallelic loci in small samples. However, previous observations have suggested that for independent loci, in small samples these statistics might produce values that more frequently lie on one side rather than on the other side of zero. Here we investigate the sampling properties of the IIS excess. We find that for any pair of independent polymorphic loci, as sample size n approaches infinity, the sampling distribution of the IIS excess approaches a normal distribution. For large samples, the IIS excess tends towards symmetry around zero, and the probabilities of positive and of negative IIS excess both approach 1/2. Surprisingly, however, we also find that for sufficiently large n, independent loci can be chosen so that the probability of a sample having positive IIS excess is arbitrarily close to either 0 or 1. The results are applied to interpretation of data from human populations, and we conclude that before employing homozygosity-based statistics to measure LD in a particular sample, especially for loci with either very small or very large homozygosities, it is useful to verify that loci with the observed homozygosity values are not likely to produce a large bias in IIS excess in samples of the given size.