Expression data from pure/mixed brain, liver and lung to test feasability and sensitivity of statistical deconvolution

To test the relationship between measured gene expression in mixed samples and the expression of genes in the isolated pure subsets, we begin with a situation in which all factors are known. Tissue samples from the brain, liver and lung of a single rat were analyzed using expression arrays (Affymetrix) in triplicate. Homogenates of those three tissues were then mixed together at the cRNA level. We then measured the gene expression pattern of each mixed sample. Such mixtures mimic the common scenario in which biological samples in a dataset are heterogeneous and vary in the relative frequency of the component subsets from one another.