Transformations, background estimation, and process effects in the statistical analysis of microarrays
Transformations, background estimation, and process effects in the statistical analysis of microarrays
复制标题
DOI：
10.1016/s0167-9473(03)00069-0
复制
发表时间：
2003-10-28
影响因子：
1.8
通讯作者：
Phang, T
中科院分区：
文献类型：
--
作者：
Kafadar, K;Phang, T
微阵列技术提供了大数据集，可以提供细胞接受各种处理时基因表达的信息。在进行正式的统计分析之前，应考虑许多生物学和程序方面的问题。这些方面可以指导分析和随后的统计推断。其中一些问题将结合寡核苷酸和 cDNA 微阵列实验的分析进行讨论。本文特别关注 cDNA 载玻片制造过程、数据的适当转换以及背景调整所造成的影响。提出了微阵列数据分析的方案，并使用比较两种小鼠细胞系基因表达的 cDNA 实验数据进行了论证；确定一组候选基因以供进一步研究。可以针对寡核苷酸微阵列数据修改处方。 (C) 2003 Elsevier B.V. 保留所有权利。
Microarray technology has made available large data sets that can provide information on gene expression when cells are subjected to various treatments. Before proceeding with a formal statistical analysis, many biological and procedural aspects should be considered. These aspects may guide the analysis and subsequent statistical inference. Several of these issues are discussed in connection with the analysis of oligonucleotide and cDNA microarray experiments. The particular focus in this article is on effects caused by the cDNA slide manufacturing process, appropriate transformations of the data, and on adjustments for background. A prescription for the analysis of microarray data is proposed and demonstrated using data from a cDNA experiment comparing the genetic expressions in two mouse cell lines; a candidate set of genes is identified for further study. The prescription may be modified for oligonucleotide microarray data. (C) 2003 Elsevier B.V. All rights reserved.