Meg Gelder Ehm, Robert W. Cottingham, Marek Kimmel,
Alejandro Schaffer, Ramana Idury, Shriram Krishnamurthi, Sandeep Gupta, G.
When pedigree marker data are obtained by typing individuals, the observed genot
is equal to the true genotype unless a typing error has occurred.
We represent error in pedigree data as incomplete penetrance of genotypes.
The observed genotypes are considered phenotypes and may not correspond to
the true genotypes due to errors. Therefore, modeling error in pedigree
data is easily accomplished using the likelihood method of genetic linkage
analysis by altering the penetrance function. Our method is designed to
identify individuals and loci likely to contain errors. The method is
equivalent to a hypothesis test for error for each individual and locus
in the pedigree. Each hypothesis test entails: (1) specifying a penetrance
function based on an assumed error rate, (2) calculating the difference
between the log-likelihood of the data at the maximum likelihood estimates
of theta assuming complete penetrance (i.e. no errors) and the log-likelihood of
the data at the maximum likelihood estimates of theta assuming incomplete
penetrance (errors possible), (3) identifying test statistics with relatively
large values as indicative of an unlikely genotype since large values are associ
with more evidence for errors than for no errors. The GenoCheck program
implements steps (1)-(3). Its output is a file containing the values of the
test statistic ranked in decreasing order.
genetic linkage analysis
UNIX platform (other platforms will be added as