Scalable Statistical Methods for Ancestral Inference from Genomic Variation Data
作者:Andrew Chan 作者单位:EECS Department, University of California, Berkeley 加工时间:2015-03-29 信息来源:EECS 索取原文[107 页]
关键词:基因组;变异; 马尔科夫链蒙特卡罗;序贯重要性采样;粒子滤波 摘 要:We develop a method using reversible jump MCMC to infer genome-wide variable recombination rates and apply it to data from two Drosophila melanogaster populations. In addition, we describe a particle filtering method to sample genealogies from the posterior distribution.