LAMARC 2.0: maximum likelihood and Bayesian estimation of population parameters

被引：531
|
作者：
Kuhner, MK [1 ]
机构：
[1] Univ Washington, Dept Genome Sci, Seattle, WA 98195 USA
来源：
BIOINFORMATICS | 2006年 / 22卷 / 06期
关键词：
D O I：
10.1093/bioinformatics/btk051
中图分类号：
Q5 [生物化学];
学科分类号：
071010 ; 081704 ;
摘要：
We present a Markov chain Monte Carlo coalescent genealogy sampler, LAMARC 2.0, which estimates population genetic parameters from genetic data. LAMARC can co-estimate subpopulation Theta = 4N(e)mu, immigration rates, subpopulation exponential growth rates and overall recombination rate, or a user-specified subset of these parameters. It can perform either maximum-likelihood or Bayesian analysis, and accomodates nucleotide sequence, SNP, microsatellite or elecrophoretic data, with resolved or unresolved haplotypes. It is available as portable source code and executables for all three major platforms.
引用
收藏
页码：768 / 770
页数：3
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