Get access

Assessing the power of informative subsets of loci for population assignment: standard methods are upwardly biased

Authors

  • E. C. ANDERSON

    1. Fisheries Ecology Division, Southwest Fisheries Science Center, 110 Shaffer Road, Santa Cruz, CA 95060, USA and Department of Applied Mathematics and Statistics, University of California, Santa Cruz, CA, USA
    Search for more papers by this author

Eric C. Anderson, Fax: (831) 420 3977; E-mail: eric.anderson@noaa.gov

Abstract

It is well known that statistical classification procedures should be assessed using data that are separate from those used to train the classifier. This principle is commonly overlooked when the classification procedure in question is population assignment using a set of genetic markers that were chosen specifically on the basis of their allele frequencies from amongst a larger number of candidate markers. This oversight leads to a systematic upward bias in the predicted accuracy of the chosen set of markers for population assignment. Three widely used software programs for selecting markers informative for population assignment suffer from this bias. The extent of this bias is documented through a small set of simulations. The relative effect of the bias is largest when screening many candidate loci from poorly differentiated populations. Simple unbiased methods are presented and their use encouraged.

Get access to the full text of this article

Ancillary