Figure 2
From: Shape-IT: new rapid and accurate algorithm for haplotype inference
Representation of the execution trellis of the hidden Markov model used to compute the probability of a haplotype. The haplotypes h1,..., h2n-2denote the previously sampled haplotypes which are used to compute the probability of the observed haplotype h. The sets {o1,..., o s } and {q1(k), ..., q s (k)} correspond respectively to the observed state sequence of haplotype h and to the hidden state sequence of haplotype h k . The transition probability a j (k,l) corresponds to the probability of jumping from hidden state q j (k) of haplotype h k to hidden state qj+1(l) of haplotype h l , and the emission probability b j (k) corresponds to the probability of observing o j given the hidden state q j (k). To compute the probability of observing the sequence h = {o1, ..., o s } in this HMM, one must sum up the probabilities of observing h over all (2n - 2)spossible sequences of s hidden states which is done efficiently by the forward algorithm.