Statistical Analysis of Exon Arrays

描述（由申请人提供）：我们建议开发新一代基因表达微阵列的统计分析方法和软件工具。这些新的阵列是探针丰富的，因为它们提供了多个探针来测量基因组中每个已知或预测的外显子的相对丰度。由于转录本上的探针数量多且位置均匀，我们现在可以在外显子水平上获得基因表达的全基因组调查。这将使我们能够研究新的生物学问题，如选择性剪接，这是前几代阵列无法评估的。这一研究结果将具有重大的生物学和医学意义，因为很大比例的人类基因是选择性剪接的，许多疾病都与剪接异常有关。我们将使用Affytron Exon 1.0 ST阵列和下一代Affytron Exon阵列作为我们研究的激励示例。我们将开发用于背景噪声校正和模拟交叉杂交效应的方法。结合这些与探针选择策略，我们将设计一个基因水平的表达指数的基因表达的定量评估。将设计用于鉴定新的和/或可变剪接的外显子以及用于检测差异剪接的方法。在这项研究中产生的数据和软件将免费提供给公众使用。公共卫生相关性：该项目将导致用于分析探针丰富的微阵列的新方法和软件。这将使研究人员能够获得更好的定量基因表达测量，并研究新的生物学问题，如选择性剪接。预计许多对改善公共卫生至关重要的基础和转化生物医学研究将受益于该项目的成果。

DESCRIPTION (provided by applicant): We propose to develop methods and software tools for the statistical analysis of a new generation of gene expression microarrays. These new arrays are probe-rich in the sense that they provide multiple probes to measure the relative abundance of each and every known or predicted exon in the genome. Because of the large number and uniform placement of probes on the transcript, we can now obtain genome-wide survey of gene expression at the exon level. This will enable us to investigate new biological questions, such as alternative splicing, that were not assessable by previous generations of arrays. The result of this research will have great biological and medical significance as a large percentage of human genes are alternatively spliced and many diseases are linked to aberrations in splicing. We will use the Affymetrix Exon 1.0 ST arrays and next-generation Affymetrix Exon arrays as the motivating example for our research. We will develop methods for background noise corrections and for modeling cross-hybridization effects. Combining these with a probe-selection strategy, we will design a gene-level expression index for quantitative assessment of gene expression. Methods will be designed for the identification of new and /or alternatively spliced exons, and for the detection of differential splicing. Data and software generated in this research will be made freely available for public use. PUBLIC HEALTH RELEVANCE: This project will lead to new methods and software for the analysis of probe-rich microarrays. This will allow researchers to obtain better quantitative gene expression measurements and to study new biological questions such as alternative splicing. It is expected that many basic and translational biomedical studies critical for the improvement of public health will benefit from the results of this project.