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

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

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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....

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Bibliographic Details
Main Authors:	Alberto Cassese, Michele Guindani, Marina Vannucci
Format:	Article
Language:	English
Published:	SAGE Publishing 2014-01-01
Series:	Cancer Informatics
Online Access:	https://doi.org/10.4137/CIN.S13784

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