DOI: 10.5061/dryad.4pv20
title: Data from: Effects of sampling close relatives on some elementary population genetics analyses

description: Many molecular ecology analyses assume the genotyped individuals are
 sampled at random from a population and thus are representative of the
 population. Realistically, however, a sample may contain excessive close
 relatives (ECR) because, for example, localized juveniles are drawn from
 fecund species. Our knowledge is limited about how ECR affect the
 routinely conducted elementary genetics analyses, and how ECR are best
 dealt with to yield unbiased and accurate parameter estimates. This study
 quantifies the effects of ECR on some popular population genetics analyses
 of marker data, including the estimation of allele frequencies,
 F-statistics, expected heterozygosity (He), effective and observed numbers
 of alleles, and the tests of Hardy-Weinberg equilibrium (HWE) and linkage
 equilibrium (LE). It also investigates several strategies for handling ECR
 to mitigate their impact and to yield accurate parameter estimates. My
 analytical work, assisted by simulations, shows that ECR have large and
 global effects on all of the above marker analyses. The naïve approach of
 simply ignoring ECR could yield low-precision and often biased parameter
 estimates, and could cause too many false rejections of HWE and LE. The
 bold approach, which simply identifies and removes ECR, and the cautious
 approach, which estimates target parameters (e.g. He) by accounting for
 ECR and using naïve allele frequency estimates, eliminate the bias and the
 false HWE and LE rejections, but could reduce estimation precision
 substantially. The likelihood approach, which accounts for ECR in
 estimating allele frequencies and thus target parameters relying on allele
 frequencies, usually yields unbiased and the most accurate parameter
 estimates. Which of the four approaches is the most effective and
 efficient may depend on the particular marker analysis to be conducted.
 The results are discussed in the context of using marker data for
 understanding population properties and marker properties.
description: Allele frequency
 simulation codeFortran source code for
 simulating genotype data, for estimating allele frequencies by different
 methods from the data, and for assessing the accuracy of different
 methodsAlleleFre.f90Allele frequency simulation executableThe compiled executable of file AlleleFre.f90AlleleFre.exeFst simulation codeFortran source code for simulating genotype data, estimating Fst by using estimated allele frequencies from different methods, and for assessing the accuracy of different methodsFst.f90fst simulation executableCompiled from file Fst.f90fst.exeHe simulation codeFortran code for simulating genotype data, estimating expected heterozygosity from the data by different methods, and assessing the accuracy of different methodsHe.f90He simulation executableCompiled from He.f90He.exeHWE Test simulation codeFortran code for simulating genotype data and testing Hardy-Weinberg equilibrium from the dataHWE_Test.f90HWE test simulation executableCompiled from HWE_test.f90hwe_test.exeLD Test simulation codeFortran code for simulating genotype data, testing linkage disequilibrium.LD_Test.f90LD Test simulation executableCompiled from LD_test.f90LD_test.exe