Statistical Analysis of Exon Arrays

描述(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。这些新的阵列是富含探针的，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。由于转录本上的大量和均匀放置的探针，我们现在可以在外显子水平上获得全基因组的基因表达调查。这将使我们能够研究新的生物学问题，例如替代剪接，这些问题是前几代阵列无法评估的。这项研究的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交替剪接的，许多疾病与剪接过程中的异常有关。我们将使用Affymetrix Exon 1.0 ST阵列和新一代Affymetrix Exon阵列作为我们研究的激励示例。我们将开发背景噪声校正和交叉杂交效果建模的方法。结合探针选择策略，我们将设计一个基因水平的表达指数来定量评估基因的表达。将设计方法来鉴定新的和/或选择性剪接的外显子，并检测差异剪接。这项研究产生的数据和软件将免费提供给公众使用。与公共卫生相关：该项目将导致分析富含探针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性生物医学研究将受益于该项目的结果。

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.