ABC as a flexible framework to estimate demography over space and time: some cons, many pros 论文

2010Molecular Ecology引用 465
Markov Chains and Monte Carlo MethodsBayesian Methods and Mixture ModelsStochastic processes and statistical mechanics

详细信息

发表期刊/会议
Molecular Ecology
发表日期
2010-06-18
发表年份
2010

关键词

Markov Chains and Monte Carlo MethodsBayesian Methods and Mixture ModelsStochastic processes and statistical mechanics

摘要

The analysis of genetic variation to estimate demographic and historical parameters and to quantitatively compare alternative scenarios recently gained a powerful and flexible approach: the Approximate Bayesian Computation (ABC). The likelihood functions does not need to be theoretically specified, but posterior distributions can be approximated by simulation even assuming very complex population models including both natural and human-induced processes. Prior information can be easily incorporated and the quality of the results can be analysed with rather limited additional effort. ABC is not a statistical analysis per se, but rather a statistical framework and any specific application is a sort of hybrid between a simulation and a data-analysis study. Complete software packages performing the necessary steps under a set of models and for specific genetic markers are already available, but the flexibility of the method is better exploited combining different programs. Many questions relevant in ecology can be addressed using ABC, but adequate amount of time should be dedicated to decide among alternative options and to evaluate the results. In this paper we will describe and critically comment on the different steps of an ABC analysis, analyse some of the published applications of ABC and provide user guidelines.