Integrative regression network for genomic association study.

ABSTRACT:

Background

The increasing availability of multiple types of genomic profiles measured from the same cancer patients has provided numerous opportunities for investigating genomic mechanisms underlying cancer. In particular, association studies of gene expression traits with respect to multi-layered genomic features are highly useful for uncovering the underlying mechanism. Conventional correlation-based association tests are limited because they are prone to revealing indirect associations. Moreover, integration of multiple types of genomic features raises another challenge.

Methods

In this study, we propose a new framework for association studies called integrative regression network that identifies genomic associations on multiple high-dimensional genomic profiles by taking

SUBMITTER: Vangimalla RR 

PROVIDER: S-EPMC4989890 | biostudies-literature | 2016 Aug

REPOSITORIES: biostudies-literature