A comprehensive method for genome scans.
In applications involving the use of genome scans the problem of correcting for multiple testing figures prominently. A frequently used approach is the Bonferroni adjustment, but this is known to be often severely conservative. As an alternative we use the method of importance sampling to accurately and efficiently obtain required exceedance probabilities. This method is comprehensive in the sense that it has application to exceedance probabilities for other classes of test statistics, such as those for linkage disequilibrium or Hardy-Weinberg equilibrium at multiple loci. We illustrate the importance sampling technique by focusing on affected sib pair tests done at a large number of fully informative markers. We demonstrate how our approach can be used to obtain exceedance probabilities for arbitrary marker spacings, and we compare our approach with that of Feingold et al. [1993], which uses the method of large deviations and does not provide the means for adjusting for unequal marker spacing.
Malley
James D
JD
Center for Information Technology, NIH, Bethesda, Md., USA.
Naiman
Daniel Q
DQ
Bailey-Wilson
Joan E
JE
D008040:Genetic Linkage; D015894:Genome, Human; D006801:Humans; D008957:Models, Genetic; D015233:Models, Statistical; D009010:Monte Carlo Method; D011336:Probability; D015203:Reproducibility of Results; D015983:Selection Bias