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Estimating Relatedness in the Presence of Null Alleles
Authors:Kang Huang  Kermit Ritland  Derek W. Dunn  Xiaoguang Qi  Songtao Guo  Baoguo Li
Affiliation:*Shaanxi Key Laboratory for Animal Conservation, and College of Life Sciences, Northwest University, Xi’an, Shaanxi 710069, China;Department of Forest and Conservation Sciences, University of British Columbia, Vancouver, British Columbia V6T 1Z4, Canada
Abstract:Studies of genetics and ecology often require estimates of relatedness coefficients based on genetic marker data. However, with the presence of null alleles, an observed genotype can represent one of several possible true genotypes. This results in biased estimates of relatedness. As the numbers of marker loci are often limited, loci with null alleles cannot be abandoned without substantial loss of statistical power. Here, we show how loci with null alleles can be incorporated into six estimators of relatedness (two novel). We evaluate the performance of various estimators before and after correction for null alleles. If the frequency of a null allele is <0.1, some estimators can be used directly without adjustment; if it is >0.5, the potency of estimation is too low and such a locus should be excluded. We make available a software package entitled PolyRelatedness v1.6, which enables researchers to optimize these estimators to best fit a particular data set.
Keywords:relatedness coefficient   null alleles   method-of-moment   maximum likelihood
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