Statistical confidence for likelihood-based paternity inference in natural populations

Authors


  • CERVUS 1.0 for Windows 95 is available from the authors. Starting with text-based genetic data, CERVUS determines allele frequencies, performs simulations and analysis paternity in study populations within a single easy-to-use Windows framework, with comprehensive on-line help. CERVUS can be downloaded from http://helios.bto.ed.ac.uk/evolgen/ or can be obtained by E-mailing the corresponding author. If neither of these methods is possible, a 3.5" floppy disk can be sent to the corresponding author. Note that not all the analyses presented in this paper can be carried out with the release version of the program.

T. C. Marshall Fax: +44 (0)131650 6564; E-mail: tristan.marshall@ed.ac.uk.

Abstract

Paternity inference using highly polymorphic codominant markers is becoming common in the study of natural populations. However, multiple males are often found to be genetically compatible with each offspring tested, even when the probability of excluding an unrelated male is high. While various methods exist for evaluating the likelihood of paternity of each nonexcluded male, interpreting these likelihoods has hitherto been difficult, and no method takes account of the incomplete sampling and error-prone genetic data typical of large-scale studies of natural systems. We derive likelihood ratios for paternity inference with codominant markers taking account of typing error, and define a statistic Δ for resolving paternity. Using allele frequencies from the study population in question, a simulation program generates criteria for Δ that permit assignment of paternity to the most likely male with a known level of statistical confidence. The simulation takes account of the number of candidate males, the proportion of males that are sampled and gaps and errors in genetic data. We explore the potentially confounding effect of relatives and show that the method is robust to their presence under commonly encountered conditions. The method is demonstrated using genetic data from the intensively studied red deer (Cervus elaphus) population on the island of Rum, Scotland. The Windows-based computer program, CERVUS, described in this study is available from the authors. CERVUS can be used to calculate allele frequencies, run simulations and perform parentage analysis using data from all types of codominant markers.

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