Mohapatra Saroj K, Krishnan Arjun
Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, VA, USA.
Methods Mol Biol. 2011;678:27-43. doi: 10.1007/978-1-60761-682-5_3.
Gene expression profiling has revolutionized functional genomics research by providing a quick handle on all the transcriptional changes that occur in the cell in response to internal or external perturbations or developmental programs. Microarrays have become the most popular technology for recording gene expression profiles. This chapter describes all the necessary steps for analyzing Affymetrix microarray data using the open-source statistical tools (R and bioconductor). The reader is walked through all the basic steps of data analysis: reading raw data, assessing quality, preprocessing/normalization, discovery of differentially expressed genes, comparison of gene lists, functional enrichment analysis, and saving results to files for future reference. Some familiarity with computer is assumed. This chapter is self-contained with installation instructions for R and bioconductor packages along with links to downloadable data and code for reproducing the examples.
基因表达谱分析通过快速掌握细胞内响应内部或外部扰动或发育程序而发生的所有转录变化,彻底改变了功能基因组学研究。微阵列已成为记录基因表达谱最流行的技术。本章介绍了使用开源统计工具(R和生物导体)分析Affymetrix微阵列数据的所有必要步骤。读者将逐步了解数据分析的所有基本步骤:读取原始数据、评估质量、预处理/归一化、发现差异表达基因、比较基因列表、功能富集分析以及将结果保存到文件以供将来参考。假定读者对计算机有一定的了解。本章自成一体,包含R和生物导体软件包的安装说明以及可下载数据的链接和用于重现示例的代码。