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Pseudo-likelihood analysis of codon substitution models with neighbor-dependent rates

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J Comput Biol, 12 (9): 1166-1182 (ноября 2005)
DOI: 10.1089/cmb.2005.12.1166

Аннотация

Recently, Markov processes for the evolution of coding DNA with neighbor dependence in the instantaneous substitution rates have been considered. The neighbor dependency makes the models analytically intractable, and previously Markov chain Monte Carlo methods have been used for statistical inference. Using a pseudo-likelihood idea, we introduce in this paper an approximative estimation method which is fast to compute. The pseudo-likelihood estimates are shown to be very accurate, and from analyzing 348 human-mouse coding sequences we conclude that the incorporation of a CpG effect improves the fit of the model considerably. plr: The pseudolikelihood uses the probability that a given codon changes from x to y with the neighboring two nucleotides either fixed or undergoing a single transition halfway down the branch.

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