Genome-wide sparse canonical correlation of gene expression with genotypes.

ABSTRACT: There is a growing interest in studying natural variation in human gene expression. Studies mapping genetic determinants of expression profiles are often carried out considering the expression of one gene at a time, an approach that is computationally intensive and may be prone to high false-discovery rate because the number of genes under consideration often exceeds tens of thousands. We present an exploratory method for investigating such data and apply it to the data provided as Problem 1 of Genetic Analysis Workshop 15 (GAW15). In multivariate analysis, canonical correlation analysis is a common way to inspect the relationship between two sets of variables based on their correlation. It determines linear combinations of all variables from each data set such that the correlation between

SUBMITTER: Parkhomenko E 

PROVIDER: S-EPMC2367499 | biostudies-literature | 2007

REPOSITORIES: biostudies-literature