Allele-sharing among affected relatives: non-parametric methods for identifying genes

Non-parametric linkage analysis examines similarities among affected relati ves in alleles of one or more genetic markers (pieces of DNA at known locat ions on a chromosome). The objective is to evaluate departures from the nul l hypothesis that the markers are not near a disease gene. Under the null h ypothesis, Mendel's laws give the probabilities that a set of relatives exh ibits a particular allele-sharing pattern, and the null hypothesis is rejec ted if the extent of allele sharing among affected relatives exceeds Mendel ian expectation. Because the rationale for allele-sharing methods is intuit ively plausible and easily grasped, geneticists have used these methods for more than 30 years, well before the advent of the large sets of polymorphi c markers that have made linkage analysis so fruitful today. Here we descri be methods for assessing whether the extent of marker allele sharing among affected relatives exceeds Mendelian expectation. We first quantify the not ion of allele sharing and the probabilities of allele sharing in various se ts of relatives. Then we describe allele sharing methods for affected sibs and more general sets of relatives. We also discuss related issues of test size and power. We conclude with a brief discussion of areas in need of fur ther research.