Empirical Bayes scan statistics for detecting clusters of disease risk variants in genetic studies.

ABSTRACT: Recent developments of high-throughput genomic technologies offer an unprecedented detailed view of the genetic variation in various human populations, and promise to lead to significant progress in understanding the genetic basis of complex diseases. Despite this tremendous advance in data generation, it remains very challenging to analyze and interpret these data due to their sparse and high-dimensional nature. Here, we propose novel applications and new developments of empirical Bayes scan statistics to identify genomic regions significantly enriched with disease risk variants. We show that the proposed empirical Bayes methodology can be substantially more powerful than existing scan statistics methods especially so in the presence of many non-disease risk variants, and in situations wh

SUBMITTER: McCallum KJ 

PROVIDER: S-EPMC4666841 | biostudies-literature | 2015 Dec

REPOSITORIES: biostudies-literature