Bjork Kathe E, Kafadar Karen
Department of Mathematical Sciences, University of Colorado at Denver and Health Sciences Center, Denver, CO 80217, USA.
Bioinformatics. 2007 Nov 1;23(21):2873-80. doi: 10.1093/bioinformatics/btm450. Epub 2007 Sep 25.
Affymetrix GeneChips are common 3' profiling platforms for quantifying gene expression. Using publicly available datasets of expression profiles from human and mouse experiments, we sought to characterize features of GeneChip data to better compare and evaluate analyses for differential expression, regulation and clustering. We uncovered an unexpected order dependence in expression data that holds across a variety of chips in both human and mouse data.
Order dependence among GeneChips affected relative expression measures pre-processed and normalized with the Affymetrix MAS5.0 algorithm and the robust multi-array average summarization method. The effect strongly influenced detection calls and tests for differential expression and can potentially significantly bias experimental results based on GeneChip profiling.
Affymetrix基因芯片是用于定量基因表达的常见3'分析平台。利用来自人类和小鼠实验的公开可用表达谱数据集，我们试图表征基因芯片数据的特征，以便更好地比较和评估差异表达、调控和聚类分析。我们在人类和小鼠数据的各种芯片中发现了表达数据中出乎意料的顺序依赖性。
基因芯片之间的顺序依赖性影响了使用Affymetrix MAS5.0算法和稳健多阵列平均汇总方法进行预处理和标准化的相对表达测量。这种影响强烈影响检测调用和差异表达测试，并可能基于基因芯片分析显著地使实验结果产生偏差。
