Statistical epistasis networks reduce the computational complexity of searching three-locus genetic models.

ABSTRACT: The rapid development of sequencing technologies makes thousands to millions of genetic attributes available for testing associations with various biological traits. Searching this enormous high-dimensional data space imposes a great computational challenge in genome-wide association studies. We introduce a network-based approach to supervise the search for three-locus models of disease susceptibility. Such statistical epistasis networks (SEN) are built using strong pairwise epistatic interactions and provide a global interaction map to search for higher-order interactions by prioritizing genetic attributes clustered together in the networks. Applying this approach to a population-based bladder cancer dataset, we found a high susceptibility three-way model of genetic variations in DNA repa

SUBMITTER: Hu T 

PROVIDER: S-EPMC3587773 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature