University of Minnesota
University Relations
http://www.umn.edu/urelate
612-624-6868

Minnesota Supercomputing Institute


Log out of MyMSI

Research Abstracts Online
January 2010 - March 2011

Main TOC ...... Next Abstract

University of Minnesota Twin Cities
School of Public Health
Division of Biostatistics

PI: Weihua Guan

Multi-Marker Test for Genetic Association

For many complex diseases or traits, the combined effects of associated genetic factors explain only a small proportion of the genetic variation. This "missing heritabilityā€¯ is likely to be caused in part by a combination of multiple low-penetrance genetic variants together with environmental and behavioral factors. These researchers are developing a multi-locus approach that can combine information from multiple markers in a gene or a small region of interest to increase the power of association studies. They are applying this new method to test for association between AR in recipients of kidney transplant and genetic variants genotyped in the DeKAF study. If AR-predisposing variants can be successfully identified, it will potentially allow for individualizing immunosuppression and gain better insight into mechanisms of AR. The researchers use MSI resources to carry out extensive computer simulations to evaluate the false positive rate and power of the proposed method, and compared the results to other multi-marker tests. They also apply their approach to the DeKAF genetic study to identify potential genetic variants predisposing to AR (and other endpoints).

Group Members

Ann M. Brearley, Staff
Lingzhi Li, Graduate Student
David Schladt, Graduate Student