Journal
MOLECULAR ECOLOGY RESOURCES
Volume 10, Issue 4, Pages 701-710Publisher
WILEY
DOI: 10.1111/j.1755-0998.2010.02846.x
Keywords
assignment test; cross-validation; holdout data; training data
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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.
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