Harr Bettina, Schlötterer Christian
Institut für Genetik, Universität Köln, Zülpicherstrasse 47, 50674 Köln, Germany.
Nucleic Acids Res. 2006 Jan 23;34(2):e8. doi: 10.1093/nar/gnj010.
Oligonucleotide microarrays are an informative tool to elucidate gene regulatory networks. In order for gene expression levels to be comparable across microarrays, normalization procedures have to be invoked. A large number of methods have been described to correct for systematic biases in microarray experiments. The performance of these methods has been tested only to a limited extend. Here, we evaluate two different types of microarray analyses: (i) the same gene in replicate samples and (ii) different, but co-expressed genes in the same sample. The reliability of the latter analysis needs to be determined for the analysis of regulatory networks and our report is the first attempt to evaluate for the accuracy of different microarray normalization methods in this respect. Consistent with previous results we observed a large effect of the normalization method on the outcome of the expression analyses. Our analyses indicate that different normalization methods should be performed depending on whether a study is aiming to detect differential gene expression between independent samples or whether co-expressed genes should be identified. We make recommendations about the most appropriate method to use.
寡核苷酸微阵列是阐明基因调控网络的一种信息丰富的工具。为了使基因表达水平在不同微阵列之间具有可比性，必须采用标准化程序。已经描述了大量方法来校正微阵列实验中的系统偏差。这些方法的性能仅在有限程度上得到了测试。在这里，我们评估两种不同类型的微阵列分析：（i）重复样本中的相同基因，以及（ii）同一样本中不同但共表达的基因。对于调控网络分析，需要确定后一种分析的可靠性，而我们的报告是在这方面评估不同微阵列标准化方法准确性的首次尝试。与先前的结果一致，我们观察到标准化方法对表达分析结果有很大影响。我们的分析表明，应根据研究目的是检测独立样本之间的差异基因表达还是识别共表达基因来选择不同的标准化方法。我们对最适合使用的方法提出了建议。
