Computational expression deconvolution in a complex mammalian organ

Background: Microarray expression profiling has been widely used to identify differentially expressed genes in complex cellular systems. However, while such methods can be used to directly infer intracellular regulation within homogeneous cell populations, interpretation of in vivo gene expression data derived from complex organs composed of multiple cell types is more problematic. Specifically, observed changes in gene expression may be due either to changes in gene regulation within a given cell type or to changes in the relative abundance of expressing cell types. Consequently, bona fide changes in intrinsic gene regulation may be either mimicked or masked by changes in the relative proportion of different cell types. To date, few analytical approaches have addressed this problem. Results: We have chosen to apply a computational method for deconvoluting gene expression profiles derived from intact tissues by using reference expression data for purified populations of the constituen...

• Type: Journal
• Year: 2006
• Where: BMCBI
• Authors: Min Wang, Stephen R. Master, Lewis A. Chodosh
• Keywords: BMCBI 2006, Cell Types, Gene Expression, Gene Regulation