LAMARC 2.0: maximum likelihood and Bayesian estimation of population parameters
LAMARC 2.0: maximum likelihood and Bayesian estimation of population parameters
复制标题
DOI：
10.1093/bioinformatics/btk051
复制
发表时间：
2006-03-15
期刊：
影响因子：
5.8
通讯作者：
Kuhner, MK
中科院分区：
文献类型：
--
作者：
Kuhner, MK
我们提出了一个马尔可夫链蒙特卡罗结合系谱采样器，LAMARC 2.0，估计群体遗传参数的遗传数据。LAMARC可以共同估计亚群Theta = 4N（e）mu，移民率，亚群指数增长率和总重组率，或这些参数的用户指定的子集。它可以进行最大似然或贝叶斯分析，并容纳核苷酸序列，SNP，微卫星或电泳数据，解决或未解决的单倍型。它作为可移植的源代码和可执行文件可用于所有三个主要平台。
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.