ANALYSIS OF OLIGONUCLEOTIDE GENE EXPRESSION ARRAY DATA

高密度寡核苷酸阵列提供了一种同时监测数万个基因表达水平的方法。这项技术产生的大量数据将是一个关键的信息来源，有助于阐明人类基因组计划中确定的大量基因的作用、功能和调控。本项目的长期目标是开发统计方法和计算机程序，用于有效分析高密度寡核苷酸阵列的基因表达数据。具体而言，我们的施舍如下。1)改进原始图像数据的分析方法，包括动态网格化和去模糊、细胞强度和质量分数的计算、背景和梯度校正。2)为数组间比较设计规范化程序。3)通过对大型表达阵列数据库的分析，学习和积累有关探针特异性效应的统计知识。这方面的知识将被利用设计的分析方法，将大大减少变异性，由于探针的影响，在估计和比较基因表达水平。这些知识也将用于设计基于模型的方法来评估基因的存在和差异表达。此外，探针序列信息将被纳入分析时，它变得可用4）开发基于上述方法学研究的计算机程序。这些程序将提供给研究界，以促进寡核苷酸表达阵列数据的有效分析。利用目前的分析方法，寡核苷酸阵列技术的非常高的固有灵敏度尚未完全实现用于基因表达研究。在这个项目中开发的方法将允许改进的分析，并将大大提高表达阵列数据的实用性。

High-density oligonucleotide arrays provide a means to monitor the expression levels of tens of thousands of genes simultaneously. The massive amount of data generated by this technology will be a key source of information that will help to clarify the roles, functions and regulation of the large number of genes identified in the Human Genome Project. The long-term objective of this project is to develop statistical methods and computer programs for effective analysis of gene expression data from high-density oligonucleotide arrays. Specifically, our alms are as follow. 1) To improve on methods for the analysis of raw image data including dynamic gridding and de-blurring, computation of cell intensity and quality scores, background and gradient correction. 2) To design normalization procedures for array-to-array Comparison. 3) To learn and accumulate statistical knowledge about probe-specific effects through the analysis of a large database of expression arrays. This knowledge will be exploited to design methods of analysis that will greatly reduce variability due to probe effects in the estimation and comparison of gene expression levels. This knowledge will also be used to design model- based methods to assess gene presence and differential expression. In addition, probe sequence information will be incorporated into the analysis when it becomes available 4) To develop computer programs based on the above methodological research. Such programs will be made available to the research community to facilitate effective analysis of oligonucleotide expression array data. With current methods of analysis the very high intrinsic sensitivity of oligonucleotide array technology has not been fully realized for gene expression studies. The methods developed in this project will allow improved analysis and will greatly enhance the utility of expression array data.