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....
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
SAGE Publishing
2014-01-01
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| Series: | Cancer Informatics |
| Online Access: | https://doi.org/10.4137/CIN.S13784 |