Maximum Likelihood Estimation of Population Growth Rates Based on the Coalescent | Zendy

Mary K. Kuhner | Zendy; Jon Yamato | Zendy; Joseph Felsenstein | Zendy

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Maximum Likelihood Estimation of Population Growth Rates Based on the Coalescent

Author(s) -

Mary K. Kuhner,

Jon Yamato,

Joseph Felsenstein

Publication year - 1998

Publication title -

genetics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 2.792

H-Index - 246

eISSN - 1943-2631

pISSN - 0016-6731

DOI - 10.1093/genetics/149.1.429

Subject(s) - coalescent theory , estimator , biology , statistics , population , mutation rate , sampling bias , population size , exponential growth , sampling (signal processing) , locus (genetics) , growth rate , effective population size , population genetics , econometrics , mathematics , genetics , sample size determination , demography , genetic variation , gene , computer science , mathematical analysis , geometry , filter (signal processing) , sociology , computer vision , phylogenetic tree

We describe a method for co-estimating 4Neμ (four times the product of effective population size and neutral mutation rate) and population growth rate from sequence samples using Metropolis-Hastings sampling. Population growth (or decline) is assumed to be exponential. The estimates of growth rate are biased upwards, especially when 4Neμ is low; there is also a slight upwards bias in the estimate of 4Neμ itself due to correlation between the parameters. This bias cannot be attributed solely to Metropolis-Hastings sampling but appears to be an inherent property of the estimator and is expected to appear in any approach which estimates growth rate from genealogy structure. Sampling additional unlinked loci is much more effective in reducing the bias than increasing the number or length of sequences from the same locus.

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