Kerr M K, Churchill G A
The Jackson Laboratory, Bar Harbor, ME, USA.
Biostatistics. 2001 Jun;2(2):183-201. doi: 10.1093/biostatistics/2.2.183.
We examine experimental design issues arising with gene expression microarray technology. Microarray experiments have multiple sources of variation, and experimental plans should ensure that effects of interest are not confounded with ancillary effects. A commonly used design is shown to violate this principle and to be generally inefficient. We explore the connection between microarray designs and classical block design and use a family of ANOVA models as a guide to choosing a design. We combine principles of good design and A-optimality to give a general set of recommendations for design with microarrays. These recommendations are illustrated in detail for one kind of experimental objective, where we also give the results of a computer search for good designs.
我们研究了基因表达微阵列技术中出现的实验设计问题。微阵列实验存在多种变异来源，实验方案应确保感兴趣的效应不与附带效应混淆。结果表明，一种常用设计违反了这一原则，且通常效率低下。我们探讨了微阵列设计与经典区组设计之间的联系，并以一族方差分析模型为指导来选择设计。我们将良好设计的原则与A - 最优性相结合，给出了一套关于微阵列设计的通用建议。针对一种实验目标详细阐述了这些建议，在此我们还给出了对良好设计进行计算机搜索的结果。
