Hackl Hubert, Sanchez Cabo Fatima, Sturn Alexander, Wolkenhauer Olaf, Trajanoski Zlatko
Institute for Genomics and Bioinformatics and Christian Doppler Laboratory for Genomics and Bioinformatics, Graz University of Technology, Petersgasse 14, A-8010 Graz, Austria.
Curr Top Med Chem. 2004;4(13):1357-70. doi: 10.2174/1568026043387773.
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.
DNA微阵列技术的最新进展对生物医学研究和药物基因组学的许多领域产生了重大影响:发现新的靶点和基因、阐明复杂疾病的特征、疾病模型的转录谱分析,以及基于差异基因表达模式开发个性化优化药物。因此,需要强大的数据分析方法和适当统计检验的选择。本综述指导cDNA微阵列数据分析流程中的所有步骤,并对解释大型微阵列数据集所面临的挑战提供基本理解。