A major project of this section is the development of new statistical genetics methodology as prompted by the needs of our applied studies. This year Dr. Bailey-Wilson worked on development of several new methods. We have continued our collaboration with Dr. Silvano Presciuttini from the University of Pisa, on the development of simplified, approximate and stepwise procedures for using genetic markers to differentiate siblings and other types of relative pairs from unrelated individuals. This methodology has applications in linkage analysis and in forensics. This collaboration has also initiated a new project, development of better methods for predicting mutation carrier status for BRCA1 in Italian families and a paper has been published this year on this work. The third project, in collaboration with Dr. Jim Malley at CIT, NIH, is the development of a new method for family based association tests that appears considerably more powerful than the TDT but more robust to false positives than is case-control association. Extensive simulation studies have been performed to test the performance of this method. Two papers demonstrating the properties of this methods were recently published. The fourth project, also in collaboration with Dr. Malley and with Dr. Dan Naiman of Johns Hopkins University (on sabbatical at NHGRI with Dr. Bailey-Wilson), is an application of less conservative methods of correcting for multiple testing in human genetics analysis. This method has been applied to Genetic Analysis Workshop data and a paper was published this fiscal year. A new project to develop propensity scores in linkage analyses as a method for inclusion of covariate effects has been initiated in conjunction with Betty Doan and Yin Yao. This method appears promising in that it is generally more powerful than including the covariates directly into the model, and does not have strongly inflated Type I error rates. Two manuscripts have been submitted. Finally, work is being done in this section to improve upon the computer implementation of various existing analysis methods. These projects are ongoing.
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