A Monte Carlo procedure for two-stage tests with correlated data

One strategy for mapping disease loci using marker-disease associations is to test for association with case-control samples and follow up a positive result with a family-based test. Using a family-based test in the second st age can help provide protection against false-positive results that can res ult from use of inappropriate controls and provides assurance that associat ion identified in the first stage is occurring between linked loci. It is c rucial for this two-stage strategy that the first stage be as powerful as p ossible to detect association since only positive results are tested in the second stage. In certain situations, the power of the first-stage test can be increased by combining the case-control and family data. However, this introduces correlation between the first- and second-stage tests, and treat ing them as independent tests causes a bias. Here we propose a Monte Carlo method that accounts for the correlation and provides the correct significa nce level for the second-stage test. We also discuss the use of a two-stage procedure when doing a genome scan for the data presented in the Genetic A nalysis Workshop 9 study. Genet. Epidemiol. 18:48-62, 2000. (C) 2000 Wiley- Liss, Inc.