Statistical issues in microarray data analysis

微阵列是一种同时测量数千个基因的相对表达水平的新技术。它们允许医学研究人员在整个基因组范围内查看在特定时间在有机体的特定组织类型中哪些基因是活跃的。澳大利亚的许多生物医学和生物研究小组最近首次取消了微阵列实验，或计划在不久的将来进行微阵列实验。微阵列实验产生了大量的信息，如何提取这些信息的研究仍处于初级阶段。该项目将解决微阵列数据分析中的一些基本问题。重点不是下游分析的特殊方法，而是所有微阵列实验共同的基本问题。该项目将确定不同生物的组织样本应该如何在复杂的实验中结合起来。它将开发评估微阵列实验结果质量的方法。它将使微阵列分析对生产人工制品的敏感度降低。它将创新地利用基因表达序列分析(SAGE)来校准微阵列实验的结果，SAGE是一种更准确但更昂贵、更不太可用的技术。在该项目的生命周期内，这些结果将应用于沃尔特和伊莱扎·霍尔研究所和墨尔本大学关于血细胞发育、细胞生长和增殖、对疟疾和利什曼病寄生虫的抵抗力以及唐氏综合症的一系列实验。

Microarrays are a new technology for measuring the relative expression levels of thousands of genes simultaneously. They allow medical researchers to take a genome-wide look at which genes are active in a particular tissue type in an organism at a particular time. Many biomedical and biological research groups in Australia have recently untaken microarray experiments for the first time or are planning microarray experiments in the near future. Microarray experiments produce massive amounts of information and the study of how to extract this information is still in a fledgling state. This project will solve a number of fundamental problems in microarray data analysis. The emphasis is not on special methods of down-stream analysis but on basic issues which are common to all microarray experiments. The project will determine how tissue samples from different organisms should be combined in complex experiments. It will develop methods for evaluating the quality of results from microarray experiments. It will make microarray analysis less sensitive to production artifacts. It will make novel use of serial analysis of gene expression (SAGE), a more accurate but more expensive and less available technology, to calibrate the results of microarray experiments. The results will be applied during the lifetime of the project to a number of experiments at the Walter and Eliza Hall Institute and the University of Melbourne on blood cell development, cell growth and proliferation, resistance to malaria and leishmaniasis parasites, and Down syndrome.