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Exact Computation of Coalescent Likelihood for Panmictic and Subdivided Populations under the Infinite Sites Model
October-December 2010 (vol. 7 no. 4)
pp. 611-618
ASCII Text
x 
 
Yufeng Wu, "Exact Computation of Coalescent Likelihood for Panmictic and Subdivided Populations under the Infinite Sites Model," IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol. 7, no. 4, pp. 611-618, October-December, 2010.
 
 
BibTex
x
 
@article{ 10.1109/TCBB.2010.2,
author = {Yufeng Wu},
title = {Exact Computation of Coalescent Likelihood for Panmictic and Subdivided Populations under the Infinite Sites Model},
journal ={IEEE/ACM Transactions on Computational Biology and Bioinformatics},
volume = {7},
number = {4},
issn = {1545-5963},
year = {2010},
pages = {611-618},
doi = {http://doi.ieeecomputersociety.org/10.1109/TCBB.2010.2},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - JOUR
JO - IEEE/ACM Transactions on Computational Biology and Bioinformatics
TI - Exact Computation of Coalescent Likelihood for Panmictic and Subdivided Populations under the Infinite Sites Model
IS - 4
SN - 1545-5963
SP611
EP618
EPD - 611-618
A1 - Yufeng Wu,
PY - 2010
KW - Population genetics
KW - coalescent theory
KW - algorithms
KW - subdivided population.
VL - 7
JA - IEEE/ACM Transactions on Computational Biology and Bioinformatics
ER -
 
Yufeng Wu, University of Connecticut, Storrs
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 and are inexact. In this paper, we develop a simple method that can compute the exact coalescent likelihood for many data sets of moderate size, including real biological data whose likelihood was previously thought to be difficult to compute exactly. Our method works for both panmictic and subdivided populations. Simulations demonstrate that the practical range of exact coalescent likelihood computation for panmictic populations is significantly larger than what was previously believed. We investigate the application of our method in estimating mutation rates by maximum likelihood. A main application of the exact method is comparing the accuracy of approximate methods. To demonstrate the usefulness of the exact method, we evaluate the accuracy of program Genetree in computing the likelihood for subdivided populations.

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Index Terms:
Population genetics, coalescent theory, algorithms, subdivided population.
Citation:
Yufeng Wu, "Exact Computation of Coalescent Likelihood for Panmictic and Subdivided Populations under the Infinite Sites Model," IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol. 7, no. 4, pp. 611-618, Oct.-Dec. 2010, doi:10.1109/TCBB.2010.2
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