2014
DOI: 10.1038/hdy.2014.88
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A maximum-likelihood estimation of pairwise relatedness for autopolyploids

Abstract: Relatedness between individuals is central to ecological genetics. Multiple methods are available to quantify relatedness from molecular data, including method-of-moment and maximum-likelihood estimators. We describe a maximum-likelihood estimator for autopolyploids, and quantify its statistical performance under a range of biologically relevant conditions. The statistical performances of five additional polyploid estimators of relatedness were also quantified under identical conditions. When comparing truncat… Show more

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Cited by 34 publications
(40 citation statements)
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References 42 publications
(60 reference statements)
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“…Relatedness inference for polyploids (e.g. [59,13]) is comparable to that for polyclonal malaria samples, which arise due co-transmission and superinfection [60]. However, relatedness inference across polyclonal malaria samples is more challenging, since the equivalence of ploidy is unknown and variable.…”
Section: Discussionmentioning
confidence: 99%
See 1 more Smart Citation
“…Relatedness inference for polyploids (e.g. [59,13]) is comparable to that for polyclonal malaria samples, which arise due co-transmission and superinfection [60]. However, relatedness inference across polyclonal malaria samples is more challenging, since the equivalence of ploidy is unknown and variable.…”
Section: Discussionmentioning
confidence: 99%
“…1 For pedigrees, the reference is the founder population; more generally, it is a population at some arbitrary time-depth (reviewed in [7,2]). Two alleles that share the same allelic type are identical by state (IBS) and include those that are both IBD and not IBD [11,1,12,7,13,2]. identity-by-state (also IBS hereafter) is observed, whereas IBD is hidden.…”
Section: Introductionmentioning
confidence: 99%
“…By searching the parameter space for values of "higher order" coefficients that maximize the probability of the genotype pattern observed, maximum-likelihood parameter values can be determined (i.e., Milligan, 2003;Anderson and Weir, 2007). The efficiency of each estimator was compared using POLYRELATEDNESS V1.3 (Huang et al, 2014a) in which 1,000,000 simulations are generated to determine relationships. In each simulation, the genotypes of the first individual were randomly generated according to Hardy-Weinberg equilibrium, and that of the second individual were conditioned on the first's genotype and their relationships.…”
Section: Estimating the Pairwise Relatednessmentioning
confidence: 99%
“…A single estimator cannot fulfill the requirements of all studies. In general, estimators can be classified into twocategories:(i)methodofmomentand(ii)maximumlikelihood.Method-of-moment estimators equate sample moments with unobservable population moments and are generally unbiased but they are not optimal in terms of statistical efficiency (Huang et al 2015a). These estimators have been developed to estimate only the relatedness coefficient (e.g., Queller and Goodnight 1989;Li et al 1993;Loiselle et al 1995;Ritland 1996) or both relatedness and four-gene coefficients simultaneously (i.e., .…”
mentioning
confidence: 99%
“…The parents of each individual were randomly selected from the previous generation (some individuals may not have reproduced), resulting in a data set of 200 individuals and 20,100 dyads. The true kinship coefficient was calculated from the pedigree by a recursive algorithm (Karigl 1981), and the true Wright's relatedness was obtained using the formula r ¼ u xy = ffiffiffiffiffiffiffiffiffiffiffiffi u xx u yy p (equation 12 in Huang et al 2015a), where u xy is the kinship coefficient between x and y, and u xx is the kinship coefficient between x and itself. The frequencies of null and visible alleles were estimated by a maximum-likelihood estimator, using an EM algorithm .…”
mentioning
confidence: 99%