BNEAT: a Bayesian network method for detecting epistatic interactions in genome-wide association studies.

ABSTRACT:

Background

Detecting epistatic interactions plays a significant role in improving pathogenesis, prevention, diagnosis and treatment of complex human diseases. A recent study in automatic detection of epistatic interactions shows that Markov Blanket-based methods are capable of finding genetic variants strongly associated with common diseases and reducing false positives when the number of instances is large. Unfortunately, a typical dataset from genome-wide association studies consists of very limited number of examples, where current methods including Markov Blanket-based method may perform poorly.

Results

To address small sample problems, we propose a Bayesian network-based approach (bNEAT) to detect epistatic interactions. The proposed method also employs a Branch-and-Bou

SUBMITTER: Han B 

PROVIDER: S-EPMC3194240 | biostudies-literature | 2011

REPOSITORIES: biostudies-literature