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Title: Confidence intervals for population allele frequencies: The general case of sampling from a finite diploid population of any size
Authors: Fung T. 
Keenan K.
Keywords: allele
cell structure
controlled study
genetic association
genetic variability
mathematical model
Melitaea cinxia
population genetic structure
resource management
risk management
sample size
Confidence Intervals
Gene Frequency
Genetics, Population
Population Density
Sample Size
Issue Date: 2014
Citation: Fung T., Keenan K. (2014). Confidence intervals for population allele frequencies: The general case of sampling from a finite diploid population of any size. PLoS ONE 9 (1) : e85925. ScholarBank@NUS Repository.
Rights: Attribution 4.0 International
Abstract: The estimation of population allele frequencies using sample data forms a central component of studies in population genetics. These estimates can be used to test hypotheses on the evolutionary processes governing changes in genetic variation among populations. However, existing studies frequently do not account for sampling uncertainty in these estimates, thus compromising their utility. Incorporation of this uncertainty has been hindered by the lack of a method for constructing confidence intervals containing the population allele frequencies, for the general case of sampling from a finite diploid population of any size. In this study, we address this important knowledge gap by presenting a rigorous mathematical method to construct such confidence intervals. For a range of scenarios, the method is used to demonstrate that for a particular allele, in order to obtain accurate estimates within 0.05 of the population allele frequency with high probability (≥95%), a sample size of >30 is often required. This analysis is augmented by an application of the method to empirical sample allele frequency data for two populations of the checkerspot butterfly (Melitaea cinxia L.), occupying meadows in Finland. For each population, the method is used to derive ≥98:3% confidence intervals for the population frequencies of three alleles. These intervals are then used to construct two joint ≥95% confidence regions, one for the set of three frequencies for each population. These regions are then used to derive a ≥95% confidence interval for Jost's D, a measure of genetic differentiation between the two populations. Overall, the results demonstrate the practical utility of the method with respect to informing sampling design and accounting for sampling uncertainty in studies of population genetics, important for scientific hypothesis-testing and also for risk-based natural resource management. © 2014 Fung, Keenan.
Source Title: PLoS ONE
ISSN: 1932-6203
DOI: 10.1371/journal.pone.0085925
Rights: Attribution 4.0 International
Appears in Collections:Staff Publications

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