Bayesian hierarchical modeling of means and covariances of gene expression data within families.

ABSTRACT: We describe a hierarchical Bayes model for the influence of constitutional genotypes from a linkage scan on the expression of a large number of genes. The model comprises linear regression models for the means in relation to genotypes and for the covariances between pairs of related individuals in relation to their identity-by-descent estimates. The matrices of regression coefficients for all possible pairs of single-nucleotide polymorphisms (SNPs) by all possible expressed genes are in turn modeled as a mixture of null values and a normal distribution of non-null values, with probabilities and means given by a third-level model of SNP and trait random effects and a spatial regression on the distance between the SNP and the expressed gene. The latter provides a way of testing for cis and t

SUBMITTER: Pique-Regi R 

PROVIDER: S-EPMC2367475 | biostudies-literature | 2007

REPOSITORIES: biostudies-literature