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A rigorous analysis of population stratification with limited data

By Kamalika Chaudhuri, Eran Halperin, Satish Rao and Shuheng Zhou

Abstract

Finding the genetic factors of complex diseases such as cancer, currently a major effort of the international community, will potentially lead to better treatment of these diseases. One of the major difficulties in these studies, is the fact that the genetic components of an individual not only depend on the disease, but also on its ethnicity. Therefore, it is crucial to find methods that could reduce the population structure effects on these studies. This can be formalized as a clustering problem, where the individuals are clustered according to their genetic information. Mathematically, we consider the problem of clustering bit “feature ” vectors, where each vector represents the genetic information of an individual. Our model assumes that this bit vector is generated according to a prior probabilit

Year: 2007
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