ABSTRACT
A maximum-likelihood method for demographic inference is applied to data sets consisting of the
frequency spectrum of unlinked single-nucleotide polymorphisms (SNPs). We use simulation analyses to
explore the effect of sample size and number of polymorphic sites on both the power to reject the null
hypothesis of constant population size and the properties of two- and three-dimensional maximum-
likelihood estimators (MLEs). Large amounts of data are required to produce accurate demographic
inferences, particularly for scenarios of recent growth. Properties of the MLEs are highly dependent upon
the demographic scenario, as estimates improve with a more ancient time of growth onset and smaller
degree of growth. Severe episodes of growth lead to an upward bias in the estimates of the current
population size, and that bias increases with the magnitude of growth. One data set of African origin
supports a model of mild, ancient growth, and another is compatible with both constant population size
and a variety of growth scenarios, rejecting greater than fivefold growth beginning ⬎36,000 years ago.
Analysis of a data set of European origin indicates a bottlenecked population history, with an 85\%
population reduction occurring ⵑ30,000 years ago
%0 Journal Article
%1 adams2004maximumlikelihood
%A Adams, Alison M.
%A Hudson, Richard R.
%D 2004
%I Genetics Society of America
%J Genetics
%K demographic_inference empirical_genealogy population_genetics
%N 3
%P 1699--1712
%R 10.1534/genetics.104.030171
%T Maximum-Likelihood Estimation of Demographic Parameters Using the Frequency Spectrum of Unlinked Single-Nucleotide Polymorphisms
%U https://doi.org/10.1534%2Fgenetics.104.030171
%V 168
%X ABSTRACT
A maximum-likelihood method for demographic inference is applied to data sets consisting of the
frequency spectrum of unlinked single-nucleotide polymorphisms (SNPs). We use simulation analyses to
explore the effect of sample size and number of polymorphic sites on both the power to reject the null
hypothesis of constant population size and the properties of two- and three-dimensional maximum-
likelihood estimators (MLEs). Large amounts of data are required to produce accurate demographic
inferences, particularly for scenarios of recent growth. Properties of the MLEs are highly dependent upon
the demographic scenario, as estimates improve with a more ancient time of growth onset and smaller
degree of growth. Severe episodes of growth lead to an upward bias in the estimates of the current
population size, and that bias increases with the magnitude of growth. One data set of African origin
supports a model of mild, ancient growth, and another is compatible with both constant population size
and a variety of growth scenarios, rejecting greater than fivefold growth beginning ⬎36,000 years ago.
Analysis of a data set of European origin indicates a bottlenecked population history, with an 85\%
population reduction occurring ⵑ30,000 years ago
@article{adams2004maximumlikelihood,
abstract = {ABSTRACT
A maximum-likelihood method for demographic inference is applied to data sets consisting of the
frequency spectrum of unlinked single-nucleotide polymorphisms (SNPs). We use simulation analyses to
explore the effect of sample size and number of polymorphic sites on both the power to reject the null
hypothesis of constant population size and the properties of two- and three-dimensional maximum-
likelihood estimators (MLEs). Large amounts of data are required to produce accurate demographic
inferences, particularly for scenarios of recent growth. Properties of the MLEs are highly dependent upon
the demographic scenario, as estimates improve with a more ancient time of growth onset and smaller
degree of growth. Severe episodes of growth lead to an upward bias in the estimates of the current
population size, and that bias increases with the magnitude of growth. One data set of African origin
supports a model of mild, ancient growth, and another is compatible with both constant population size
and a variety of growth scenarios, rejecting greater than fivefold growth beginning ⬎36,000 years ago.
Analysis of a data set of European origin indicates a bottlenecked population history, with an 85\%
population reduction occurring ⵑ30,000 years ago},
added-at = {2019-09-20T20:21:02.000+0200},
author = {Adams, Alison M. and Hudson, Richard R.},
biburl = {https://www.bibsonomy.org/bibtex/26fc8ba171941c43436dd6ae86ebeef6c/peter.ralph},
doi = {10.1534/genetics.104.030171},
interhash = {728b60b07570481fb9d50abdc058732a},
intrahash = {6fc8ba171941c43436dd6ae86ebeef6c},
journal = {Genetics},
keywords = {demographic_inference empirical_genealogy population_genetics},
month = nov,
number = 3,
pages = {1699--1712},
publisher = {Genetics Society of America},
timestamp = {2019-09-20T20:21:02.000+0200},
title = {Maximum-Likelihood Estimation of Demographic Parameters Using the Frequency Spectrum of Unlinked Single-Nucleotide Polymorphisms},
url = {https://doi.org/10.1534%2Fgenetics.104.030171},
volume = 168,
year = 2004
}