Estimating allelic richness: effects of sample size and bottlenecks.
Although differences in sampling intensity can bias comparisons of allelic richness (A) among populations, investigators often fail to correct estimates of A for differences in sample size. Methods that standardize A on the basis of the size of the smallest number of samples in a comparison are preferable to other approaches. Rarefaction and repeated random subsampling provide unbiased estimates of A with the greatest precision and thus provide greatest statistical power to detect differences in variation. Less promising approaches, in terms of bias or precision, include single random subsampling, eliminating very small samples, using sample size as a covariate or extrapolating estimates obtained from small samples to a larger number of individuals.
Leberg
P L
PL
Department of Biology, University of Louisiana, Lafayette, LA 70504, USA. leberg@louisiana.edu
D000483:Alleles; D005787:Gene Frequency; D014644:Genetic Variation; D005828:Genetics, Population; D016014:Linear Models; D008957:Models, Genetic; D011897:Random Allocation; D018401:Sample Size; D015983:Selection Bias