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    Author(s): Jamie S. Sanderlin; Nicole Lazar; Michael J. Conroy; Jaxk Reeves
    Date: 2012
    Source: Journal of Wildlife Management 76(1): 88-94.
    Publication Series: Scientific Journal (JRNL)
    Station: Rocky Mountain Research Station
    PDF: Download Publication  (154.19 KB)


    Genetic techniques are frequently used to sample and monitor wildlife populations. The goal of these studies is to maximize the ability to distinguish individuals for various genetic inference applications, a process which is often complicated by genotyping error. However, wildlife studies usually have fixed budgets, which limit the number of geneticmarkers available for inclusion in a study marker panel. Prior to our study, a formal algorithm for selecting a marker panel that included genotyping error, laboratory costs, and ability to distinguish individuals did not exist. We developed a constrained nonlinear programming optimization algorithm to determine the optimal number of markers for a marker panel, initially applied to a pilot study designed to estimate black bear abundance in central Georgia. We extend the algorithm to other genetic applications (e.g., parentage or population assignment) and incorporate possible null alleles. Our algorithm can be used in wildlife pilot studies to assess the feasibility of genetic sampling for multiple genetic inference applications.

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    Sanderlin, Jamie S.; Lazar, Nicole; Conroy, Michael J.; Reeves, Jaxk. 2012. Cost-efficient selection of a marker panel in genetic studies. Journal of Wildlife Management 76(1): 88-94.


    abundance estimation, black bear, cost-efficient, genotyping error, Georgia, optimal marker panel, parentage, population assignment, Ursus americanus

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