Data from: Estimating genotyping errors from genotype and reconstructed pedigree data|基因分型错误估计数据集|家系重建数据集

1. Genotyping errors are rules rather than exceptions in reality, and are
found in virtually all but very small datasets. These errors, even when
occurring at an extremely low rate, can derail many genetic analyses such
as parentage/sibship assignments and linkage/association studies. 2.
Nonetheless, few robust and accurate methods are available for estimating
the rate of occurrence of genotyping errors and for identifying individual
erroneous genotypes at a locus. Methods based on duplicate genotyping are
expensive, and estimate genotype inconsistency rather than error rate at a
locus. Methods based on Hardy-Weinberg equilibrium tests have low
robustness and low power, and apply only to those particular errors that
cause excessive homozygosity. Methods based on pedigrees are powerful,
robust and accurate. However, they rely on known and complete pedigrees
that are unfortunately rarely available from natural populations in the
wild. 3. I proposed a maximum likelihood method to reconstruct pedigrees
from genotype data with errors occurring at a roughly estimated (presumed)
rate. In this paper, I describe how to use the method and inferred
pedigree in estimating allelic dropout (or null allele) rate and false
allele rate jointly at each marker locus, in identifying the erroneous
genotypes, and in inferring the most likely genotypes at each locus of
each individual. I examine the power, accuracy and robustness of the
method by extensive simulations, and demonstrate the usefulness of the
method by analysing three empirical datasets. 4. It is concluded that,
both pedigrees and the rates of genotyping errors at each locus can be
reliably estimated from the same genotype data by the same likelihood
method, when marker information is sufficient and some sampled individuals
are first-degree relatives. The erroneous genotypes are however inferred
conservatively, and are reliably detected only when they occur in large
families and/or at highly polymorphic loci. Estimation of genotyping error
rates per locus and identification of erroneous genotypes of each
individual at each locus should be routinely conducted to assess and
improve data quality, to highlight markers for optimization of genotyping
protocols or for replacement, and to enable the integration of genotyping
errors in a robust statistical analysis.