Analysis of Oligonucleotide Gene Expression Array Data

寡核苷酸基因表达阵列数据分析

• 批准号: 6960970
• 负责人: Wing H. WONG
• 金额: $ 38.64万
• 依托单位: STANFORD UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2000
• 资助国家: 美国
• 起止时间: 2000-09-15 至 2006-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6960970
• 关键词: biotechnology; computer program /software; computer system design /evaluation; cooperative study; gene expression; human data; mathematics; method development; microarray technology; oligonucleotides; statistics /biometry

DESCRIPTION (provided by applicant): The long-term objective of this project is to develop statistical methods and computer programs for effective analysis of microarray data. The development will build on our previous work on the model-based approach to such analyses but will address several issues in order to significantly improve the performance. Our specific aims are as follows. Aim 1. To develop methods for the full modeling of the responses of perfect match and mismatch oligonucleotide probes to changes in mRNA concentration, and to exploit such models to construct estimates of improved expression indexes. By doing so, we hope to extend the linearity of the estimates to the low signal range where cross-hybridization effects must be accounted for in the estimation process. We will also investigate the feasibility of oligonucleotide expression arrays based on perfect match-only design. Aim 2. To develop array-to-array normalization methods applicable to situations when the corresponding samples are expected to exhibit very different expression patterns. Aim 3. To develop statistical methods for the analysis of tag-probe arrays for the study of mixtures of yeast mutants. Aim 4. To develop computer program modules based on the above methods, and to incorporate them into the software dChip in order to extend its functionality for model-based analysis of oligonucleotide array data. We will also work closely with experimental groups in the analysis of real data, in order to ensure that the results from our research will be relevant to the need of the user community. We will aim to improve dChip not only by the methods directly resulting from Aim 1, but will also selectively implement and incorporate other useful analysis methods developed by our group and our collaborators into the dChip framework. Aim 5. To collaborate with the R-based bioinformatics consortium to facilitate the transfer of our methodology to that platform, and to extend the functionality of dChip through R function calls.

描述（由申请人提供）：该项目的长期目标是开发用于有效分析微阵列数据的统计方法和计算机程序。该开发将建立在我们之前基于模型的分析方法的工作基础上，但将解决几个问题，以显着提高性能。我们的具体目标如下。 目标 1. 开发完全模拟完美匹配和错配寡核苷酸探针对 mRNA 浓度变化的响应的方法，并利用此类模型来构建改进表达指数的估计。通过这样做，我们希望将估计的线性扩展到低信号范围，在估计过程中必须考虑交叉杂交效应。我们还将研究基于完美匹配设计的寡核苷酸表达阵列的可行性。 目标 2. 开发适用于预期相应样本表现出非常不同的表达模式的情况的阵列到阵列标准化方法。 目标 3. 开发用于分析标签探针阵列的统计方法，以研究酵母突变体的混合物。 目标 4. 基于上述方法开发计算机程序模块，并将其合并到软件 dChip 中，以扩展其基于模型的寡核苷酸阵列数据分析的功能。我们还将与实验组密切合作，对真实数据进行分析，以确保我们的研究结果能够满足用户群体的需求。我们的目标不仅是通过目标 1 直接产生的方法来改进 dChip，而且还将有选择地实施并将我们小组和合作者开发的其他有用的分析方法纳入 dChip 框架。 目标 5. 与基于 R 的生物信息学联盟合作，促进我们的方法转移到该平台，并通过 R 函数调用扩展 dChip 的功能。