Assessing multivariate gene-metabolome associations with rare variants using Bayesian reduced rank regression.

ABSTRACT:

Motivation

A typical genome-wide association study searches for associations between single nucleotide polymorphisms (SNPs) and a univariate phenotype. However, there is a growing interest to investigate associations between genomics data and multivariate phenotypes, for example, in gene expression or metabolomics studies. A common approach is to perform a univariate test between each genotype-phenotype pair, and then to apply a stringent significance cutoff to account for the large number of tests performed. However, this approach has limited ability to uncover dependencies involving multiple variables. Another trend in the current genetics is the investigation of the impact of rare variants on the phenotype, where the standard methods often fail owing to lack of power when the mi

SUBMITTER: Marttinen P 

PROVIDER: S-EPMC4080737 | biostudies-literature | 2014 Jul

REPOSITORIES: biostudies-literature