Implementation of a generalized pair hidden Markov chain model (GPHMM) that can be used to compute the probability of alignment between two sequences of nucleotides (e.g., a reference sequence and a noisy sequenced read). The model can be trained on a dataset where the noisy sequenced reads are known to have been sequenced from known reference sequences. If no training sets are available default parameters can be used.
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