Data from: Estimation of genotyping error rate from repeat genotyping, unintentional recaptures and known parent-offspring comparisons in 16 microsatellite loci for brown rockfish (Sebastes auriculatus)

Genotyping errors are present in almost all genetic data and can affect
biological conclusions of a study, particularly for studies based on
individual identification and parentage. Many statistical approaches can
incorporate genotyping errors, but usually need accurate estimates of
error rates. Here, we used a new microsatellite data set developed for
brown rockfish (Sebastes auriculatus) to estimate genotyping error using
three approaches: (i) repeat genotyping 5% of samples, (ii) comparing
unintentionally recaptured individuals and (iii) Mendelian inheritance
error checking for known parent–offspring pairs. In each data set, we
quantified genotyping error rate per allele due to allele drop-out and
false alleles. Genotyping error rate per locus revealed an average overall
genotyping error rate by direct count of 0.3%, 1.5% and 1.7% (0.002, 0.007
and 0.008 per allele error rate) from replicate genotypes, known
parent–offspring pairs and unintentionally recaptured individuals,
respectively. By direct-count error estimates, the recapture and known
parent–offspring data sets revealed an error rate four times greater than
estimated using repeat genotypes. There was no evidence of correlation
between error rates and locus variability for all three data sets, and
errors appeared to occur randomly over loci in the repeat genotypes, but
not in recaptures and parent–offspring comparisons. Furthermore, there was
no correlation in locus-specific error rates between any two of the three
data sets. Our data suggest that repeat genotyping may underestimate true
error rates and may not estimate locus-specific error rates accurately. We
therefore suggest using methods for error estimation that correspond to
the overall aim of the study (e.g. known parent–offspring comparisons in
parentage studies).