Cell type-specific gene expression differences in complex tissues

Abstract

We describe cell type-specific significance analysis of microarrays (csSAM) for analyzing differential gene expression for each cell type in a biological sample from microarray data and relative cell-type frequencies. First, we validated csSAM with predesigned mixtures and then applied it to whole-blood gene expression datasets from stable post-transplant kidney transplant recipients and those experiencing acute transplant rejection, which revealed hundreds of differentially expressed genes that were otherwise undetectable.

Figure 1

Overview of csSAM. Different cell types are denoted by circles, diamonds and hexagons. csSAM identifies cell type–specific differential expression, as shown by the arrows on the right.

Figure 2

Statistical deconvolution of complex tissues yields accurate estimates of pure tissue-subset expression. (a–c) Density plots of estimated tissue-specific gene expression deconvoluted from mixed tissue samples plotted against measured gene expression from individual tissues. Color represents point density from a single probe (cyan) to 100 probes (yellow). RMA, robust multichip average.

Figure 3

csSAM reveals cell type–specific differential expression undetectable at heterogeneous tissue level. (a–f) Differential expression analysis in whole blood (a) and the indicated cell types (b–f) between samples from individuals with acute rejection and stable post-transplant course.