Figure 1.

(A) Hierarchical HMM state diagram for HAPAA. On the left, inter- and intra-population transitions occur with probabilities governed by matrix A(p, p′). In the middle, each population P_p has a similar structure: entry state In_p transitions with uniform probability to a diploid model individual a_pk, then to exit state Out_p. On the right, in a_pk we transition into one of two states representing the haplotypes S_pk0 and S_pk1 of model individual a_pk with equal probability. Each haplotype emits its alleles a_pkhi via a mutation/error probability distribution M(a^pkhi, a_i). Haplotypes transition to each other with probability proportional to the phase switch error W_pki, and transition out of the diploid sample with probability governed by genetic distance to the next locus R_i and the population-specific recombination rate parameter τ_p. (B) HMM state diagram for previous methods. Each state represents a population and emits alleles according to frequency estimates for the populations, and admixture transition probabilities depend on the degree of admixture expected and other learned parameters. By construction, these methods assume a greater degree of independence between adjacent loci.