One of the most important directions in current biomedical research is the quest to understand the genetic contributions to complex diseases. A critical part of many such investigations is the use of linkage analysis to find possible disease susceptibility loci. Recently, there has been substantial interest in using linkage methods designed for quantitative phenotypes as a tool for finding genes associated with diseases. For example, this approach has been applied to schizophrenia, type II diabetes, hypertension, and heart disease. This growth in interest in QTL mapping in humans has been accompanied by a great deal of new work on statistical methods, but little of that work has dealt with selected samples, which are arguably more common than population samples for human studies. The general aim of this grant is to develop powerful statistics for QTL mapping with selected samples and powerful designs for selecting such samples.
The specific aims are as follows. 1) Develop and compare statistics for selectively sampled nuclear families. 2) Develop and compare statistics for selectively sampled extended pedigrees. 3) Develop end-user software to implement all of the best methods and make them readily available to investigators doing mapping studies. 4) Investigate the relative power of different sampling schemes under various genetic models. ? ?
