Probabilistic Approaches to Alignment with Tandem Repeats
Quantitative Methods
2013-07-31 v1 Genomics
Abstract
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.
Cite
@article{arxiv.1307.7861,
title = {Probabilistic Approaches to Alignment with Tandem Repeats},
author = {Michal Nánási and Tomáš Vinař and Broňa Brejová},
journal= {arXiv preprint arXiv:1307.7861},
year = {2013}
}
Comments
Peer-reviewed and presented as part of the 13th Workshop on Algorithms in Bioinformatics (WABI2013)