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HKA was developed to be a computer program that carries out the widely used statistical test for natural selection that was developed by Hudson, R. R., M. Kreitman and M. Aguade (1987 A test of neutral molecular evolution based on nucleotide data. Genetics 116: 153-159). This program can handle very large numbers of loci and sample sizes, and conducts tests via coalescent simulation as well as by the conventional chi square approximation. The simulations can also be used to conduct other tests of natural selection, including tests of Tajima's D statistic (1989) and the D statistic of Fu and Li (1993). RATIONAL The HKA test is based on the most basic prediction of the neutral model of molecular evolution, that DNA sequence polymorphism within a species, and DNA sequence divergence between species, will be proportional to the neutral mutation rate (Kimura, 1968, 1969). To this basic expectations we must add that polymorphism also depends on the effective population size and that divergence also depends on the time since speciation. When we consider data collected from two species, and from multiple loci, we expect that all of the loci within a species will share the same effective population size, and we expect that each locus, regardless of species, will have a characteristic neutral mutation rate (depending on its length and level of selective constraint). Thus we can consider data on polymorphism and divergence cast in form of a contingency table (Figure 1). We can also build a similar table of the expected values, each a function of the basic model parameters that are fit to the data. Those parameters are: T - the time since the species divergence f - the ratio of the the two species effective population sizes. Theta_i = 4N1 u_i - the population mutation rate for locus i in species 1, where N1 - the effective population size of species 1 and u_i is the neutral mutation rate at locus i. There is one Theta parameter for every locus.

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