Abstract

Recent advances in DNA microarray technology have great impact on many areas of biomedical research and pharmacogenomics: discovering novel targets and genes, elucidating signatures of complex diseases, transcriptional profiling of models for diseases, and the development of individually optimized drugs based on differential gene expression patterns. Consequently, there is demand for robust methods for data analysis and the choice of adequate statistical tests. This review guides through all steps in the cDNA microarray data analysis pipeline and gives a basic understanding of the challenges in interpreting large microarray datasets.

Keywords: microarray, analysis, statistics, normalization, clustering