Development of statistical genetics methodology

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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. Additional development has been done on these methods this year and a paper was published. This collaboration has also initiated a new project, development of better methods for predicting mutation carrier status for BRCA1 in Italian families. A paper has been submitted presenting 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. A paper demonstrating the properties of this method on simulated data was recently published in Genetic Epidemiology and another paper Biometric Journal was published in this fiscal year. The fourth project, also in collaboration with Dr. Malley and with Dr. Dan Naiman of Johns Hopkins University, 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 13 data this year, and a paper is in press. A manuscript was also published this year detailing the theoretical basis of this work. Finally, work is being done in this section to improve upon the computer implementation of various existing analysis methods. These projects are ongoing.