Mayo Matthew S, Gajewski Byron J, Morris Jeffrey S
Department of Preventive Medicine and Public Health, Center for Biostatistics and Advanced Informatics, Kansas Masonic Cancer Research Institute.
Radiat Res. 2006 Jun;165(6):745-8. doi: 10.1667/RR3576.1.
In this paper we discuss some of the statistical issues that should be considered when conducting experiments involving microarray gene expression data. We discuss statistical issues related to preprocessing the data as well as the analysis of the data. Analysis of the data is discussed in three contexts: class comparison, class prediction and class discovery. We also review the methods used in two studies that are using microarray gene expression to assess the effect of exposure to radiofrequency (RF) fields on gene expression. Our intent is to provide a guide for radiation researchers when conducting studies involving microarray gene expression data.
在本文中，我们讨论了在进行涉及微阵列基因表达数据的实验时应考虑的一些统计学问题。我们讨论了与数据预处理以及数据分析相关的统计学问题。数据分析在三种情况下进行讨论：类别比较、类别预测和类别发现。我们还回顾了两项研究中使用的方法，这两项研究利用微阵列基因表达来评估暴露于射频（RF）场对基因表达的影响。我们的目的是为辐射研究人员在进行涉及微阵列基因表达数据的研究时提供指导。
