Mitigating scoring errors in microsatellite data from wild populations

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.