JSM 2005 - Toronto

Abstract #303122

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Activity Number: 134
Type: Contributed
Date/Time: Monday, August 8, 2005 : 10:30 AM to 12:20 PM
Sponsor: Biometrics Section
Abstract - #303122
Title: Space-Dependence of Substitution Rates: An Application of GEE and Composite Likelihood Methods
Author(s): Ling Deng*+ and Dirk F. Moore
Companies: Temple University/Novo Nordisk and University of Medicine and Dentistry of New Jersey
Address: 2618 Quail Ridge Dr, Plainsboro, NJ, 08536, United States
Keywords: Substitution rate of DNA sequences, ; heterogeneity and space-dependence ; GEE ; multivariate gamma distribution ; bivariate negative binomial distribution ; composite likelihood method
Abstract:

It is known that substitution rates of DNA sequences across sites may be effectively modeled with a gamma distribution and the numbers of substitutions at these sites follow a negative binomial distribution. Although traditional evolutionary models have assumed different sites evolve independently, much evidence shows this assumption is inaccurate. Yang (1995b) proposed a maximum likelihood method based on Markov chains to estimate the correlation of neighboring substitution rates. However, his method has three drawbacks: the estimation of the correlation parameter is based on a bivariate normal distribution rather than on a bivariate gamma distribution, it considers only a simple correlation structure, and Markov chain-type methods are good for prediction only, not for describing the whole correlation structure. In this paper, we propose a new composite likelihood method for a multivariate negative binomial distribution to overcome the above drawbacks.

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