A Bayesian Integrative Model for Genetical Genomics with Spatially Informed Variable Selection


We consider a Bayesian hierarchical model for the integration of gene expression levels with comparative genomic hybridization (CGH) array measurements collected on the same subjects. The approach defines a measurement error model that relates the gene expression levels to latent copy number states. In turn, the latent states are related to the observed… (More)
DOI: 10.4137/CIN.S13784


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