Microarray data analysis

Methods Mol Biol. 2011:678:27-43. doi: 10.1007/978-1-60761-682-5_3.

Abstract

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.

MeSH terms

  • Computational Biology / methods
  • Gene Expression Profiling / methods
  • Oligonucleotide Array Sequence Analysis / methods*
  • Software