Studying genetic determinants of natural variation in human gene expression using Bayesian ANOVA.

ABSTRACT: Standard genetic mapping techniques scan chromosomal segments for location of genetic linkage and association signals. The majority of these methods consider only correlations at single markers and/or phenotypes with explicit detailing of the genetic structure. These methods tend to be limited by their inability to consider the effect of large numbers of model variables jointly. In contrast, we propose a Bayesian analysis of variance (ANOVA) method to categorize individuals based on similarity of multidimensional profiles and attempt to analyze all variables simultaneously. Using Problem 1 of the Genetic Analysis Workshop 15 data set, we demonstrate the method's utility for joint analysis of gene expression levels and single-nucleotide polymorphism genotypes. We show that the method extrac

SUBMITTER: Cartier KC 

PROVIDER: S-EPMC2367590 | biostudies-literature | 2007

REPOSITORIES: biostudies-literature