We propose a simple tractable pair hidden Markov model for pairwise sequence alignment that accounts for the presence of short tandem repeats. Using the framework of gain functions, we design several optimization criteria for decoding this model and describe the resulting decoding algorithms, ranging from the traditional Viterbi and posterior decoding to block-based decoding algorithms specialized for our model. We compare the accuracy of individual decoding algorithms on simulated data and find our approach superior to the classical three-state pair HMM in simulations. © 2013 Springer-Verlag.
CITATION STYLE
Nánási, M., Vinař, T., & Brejová, B. (2013). Probabilistic approaches to alignment with tandem repeats. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8126 LNBI, pp. 287–299). https://doi.org/10.1007/978-3-642-40453-5_22
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