  Genotyping errors are known to influence the power of both family-based and
case-control studies in the genetics of complex disease. Estimating genotyping
error rate in a given dataset can be complex, but when family information is
available error rates can be inferred from the patterns of Mendelian
inheritance between parents and offspring. I introduce a novel likelihood-based
method for calculating error rates from family data, given known allele
frequencies. I apply this to an example dataset, demonstrating a low genotyping
error rate in genotyping data from a personal genomics company.
