Wolkenhauer Olaf, Möller-Levet Carla, Sanchez-Cabo Fatima
Department of Biomolecular Sciences, Control Systems Centre, UMIST, Manchester M60 1QD, UK.
Comp Funct Genomics. 2002;3(4):375-9. doi: 10.1002/cfg.192.
Despite its enormous promise to further our understanding of cellular processes involved in the regulation of gene expression, microarray technology generates data for which statistical pre-processing has become a necessity before any interpretation of data can begin. The process by which we distinguish (and remove) non-biological variation from biological variation is called normalization. With a multitude of experimental designs, techniques and technologies influencing the acquisition of data, numerous approaches to normalization have been proposed in the literature. The purpose of this short review is not to add to the many suggestions that have been made, but to discuss some of the difficulties we encounter when analysing microarray data.
尽管微阵列技术对于增进我们对基因表达调控中细胞过程的理解有着巨大潜力，但在开始对数据进行任何解读之前，该技术所生成的数据都需要进行统计预处理。我们从生物变异中区分（并去除）非生物变异的过程称为标准化。由于众多实验设计、技术和工艺都会影响数据的获取，文献中已经提出了许多标准化方法。这篇简短综述的目的并非增加已有的众多建议，而是讨论我们在分析微阵列数据时遇到的一些困难。
