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Mitigating scoring errors in microsatellite data from wild populations

Authors

  • JENNIFER DEWOODY,

    1. USDA Forest Service, Pacific Southwest Research Station, National Forest Genetics Laboratory, 2480 Carson Road, Placerville, California 95667, USA,
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  • JOHN D. NASON,

    1. Department of Ecology, Evolution, and Organismal Biology, Iowa State University, Ames, Iowa 50011, USA
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  • VALERIE D. HIPKINS

    1. USDA Forest Service, Pacific Southwest Research Station, National Forest Genetics Laboratory, 2480 Carson Road, Placerville, California 95667, USA,
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J. DeWoody, Fax: 530-622-2633; E-mail: jdewoody@fs.fed.us

Abstract

Microsatellite data are widely used to test ecological and evolutionary hypotheses in wild populations. In this paper, we consider three typical sources of scoring errors capable of biasing biological conclusions: stuttering, large-allele dropout and null alleles. We describe methods to detect errors and propose conventions to mitigate scoring errors and report error rates in studies of wild populations. Finally, we discuss potential bias in ecological or evolutionary conclusions based on data sets containing these scoring errors.

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