Exact Computation of Coalescent Likelihood under the Infinite Sites Model

Authors:
Yufeng Wu
Affiliations:
Department of Computer Science and Engineering, University of Connecticut, Storrs, U.S.A. CT 06269
Venue:
ISBRA '09 Proceedings of the 5th International Symposium on Bioinformatics Research and Applications
Year:
2009

Citing 2
Cited 1

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IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Accurate computation of likelihoods in the coalescent with recombination via parsimony

RECOMB'08 Proceedings of the 12th annual international conference on Research in computational molecular biology

Efficiently solvable perfect phylogeny problems on binary and k-state data with missing values

WABI'11 Proceedings of the 11th international conference on Algorithms in bioinformatics

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Abstract

Coalescent likelihood is the probability of observing the given population sequences under the coalescent model. Computation of coalescent likelihood under the infinite sites model is a classic problem in coalescent theory. Existing methods are based on either importance sampling or Markov chain Monte Carlo. In this paper, we develop a simple method that can compute the exact coalescent likelihood for many datasets of moderate size, including a real biological data whose likelihood was previously thought to be difficult to compute exactly. Simulations demonstrate that the practical range of exact coalescent likelihood computation is significantly larger than what was previously believed.