Integrated genomic analysis of biological gene sets with applications in lung cancer prognosis.

ABSTRACT:

Background

Burgeoning interest in integrative analyses has produced a rise in studies which incorporate data from multiple genomic platforms. Literature for conducting formal hypothesis testing on an integrative gene set level is considerably sparse. This paper is biologically motivated by our interest in the joint effects of epigenetic methylation loci and their associated mRNA gene expressions on lung cancer survival status.

Results

We provide an efficient screening approach across multiplatform genomic data on the level of biologically related sets of genes, and our methods are applicable to various disease models regardless whether the underlying true model is known (iTEGS) or unknown (iNOTE). Our proposed testing procedure dominated two competing methods. Using our meth

SUBMITTER: Chu SH 

PROVIDER: S-EPMC5505153 | biostudies-literature | 2017 Jul

REPOSITORIES: biostudies-literature