Department of Pediatrics, Stanford University School of Medicine, Stanford, California, USA.
Nat Methods. 2010 Apr;7(4):287-9. doi: 10.1038/nmeth.1439. Epub 2010 Mar 7.
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.
我们描述了细胞类型特异性微阵列分析（csSAM），用于分析来自微阵列数据和相对细胞类型频率的生物样本中每种细胞类型的差异基因表达。首先，我们使用预先设计的混合物验证了 csSAM，然后将其应用于稳定的肾移植后受者和发生急性移植排斥反应的全血基因表达数据集，结果发现了数百个差异表达基因，否则这些基因是无法检测到的。
