Durinck Steffen
Katholieke Universiteit Leuven, Leuven, Belgium.
Methods Mol Biol. 2008;452:89-110. doi: 10.1007/978-1-60327-159-2_4.
Microarrays have become a widely used technology in molecular biology research. One of their main uses is to measure gene expression. Compared to older expression measuring assays such as Northern blotting, analyzing gene expression data from microarrays is inherently more complex due to the massive amounts of data they produce. The analysis of microarray data requires biologists to collaborate with bioinformaticians or learn the basics of statistics and programming. Many software tools for microarray data analysis are available. Currently one of the most popular and freely available software tools is Bioconductor. This chapter uses Bioconductor to preprocess microarray data, detect differentially expressed genes, and annotate the gene lists of interest.
微阵列已成为分子生物学研究中广泛使用的技术。其主要用途之一是测量基因表达。与诸如Northern印迹等较旧的表达测量分析方法相比，由于微阵列产生的大量数据，分析来自微阵列的基因表达数据本质上更加复杂。微阵列数据分析需要生物学家与生物信息学家合作，或者学习统计学和编程的基础知识。有许多用于微阵列数据分析的软件工具。目前最流行且免费的软件工具之一是Bioconductor。本章使用Bioconductor对微阵列数据进行预处理、检测差异表达基因并注释感兴趣的基因列表。
