Cell type–specific gene expression differences in complex tissues
Nature methods, 2010•nature.com
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.
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.
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.
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