Efficient simulation and likelihood methods for non-neutral multi-allele models.
Throughout the 1980s, Simon Tavaré made numerous significant contributions to population genetics theory. As genetic data, in particular DNA sequence, became more readily available, a need to connect population-genetic models to data became the central issue. The seminal work of Griffiths and Tavaré (1994a , 1994b , 1994c) was among the first to develop a likelihood method to estimate the population-genetic parameters using full DNA sequences. Now, we are in the genomics era where methods need to scale-up to handle massive data sets, and Tavaré has led the way to new approaches. However, performing statistical inference under non-neutral models has proved elusive. In tribute to Simon Tavaré, we present an article in spirit of his work that provides a computationally tractable method for simulating and analyzing data under a class of non-neutral population-genetic models. Computational methods for approximating likelihood functions and generating samples under a class of allele-frequency based non-neutral parent-independent mutation models were proposed by Donnelly, Nordborg, and Joyce (DNJ) (Donnelly et al., 2001). DNJ (2001) simulated samples of allele frequencies from non-neutral models using neutral models as auxiliary distribution in a rejection algorithm. However, patterns of allele frequencies produced by neutral models are dissimilar to patterns of allele frequencies produced by non-neutral models, making the rejection method inefficient. For example, in some cases the methods in DNJ (2001) require 10(9) rejections before a sample from the non-neutral model is accepted. Our method simulates samples directly from the distribution of non-neutral models, making simulation methods a practical tool to study the behavior of the likelihood and to perform inference on the strength of selection.
Department of Mathematics and Initiative for Bioinformatics and Evolutionary Studies, University of Idaho, Moscow, ID, USA.
Paul
P
Joyce
Alan
A
Genz
Erkan Ozge
EO
Buzbas
D000465:Algorithms; D000483:Alleles; D003198:Computer Simulation; D005787:Gene Frequency; D005828:Genetics, Population / Q000379:methods / Q000706:statistics & numerical data*; D006801:Humans; D016013:Likelihood Functions; D008957:Models, Genetic; D009154:Mutation; D012641:Selection, Genetic; D017422:Sequence Analysis, DNA