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Analysis of Oligonucleotide Gene Expression Array Data

寡核苷酸基因表达阵列数据分析

基本信息

批准号：
6904624
负责人：
Wing H. WONG
金额：
$ 53.29万
依托单位：
STANFORD UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2000
资助国家：
美国
起止时间：
2000-09-15 至 2007-06-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/6904624
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

项目摘要

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.

项目描述：本项目的长期目标是开发有效分析微阵列数据的统计方法和计算机程序。发展将建立在我们以前的工作，基于模型的方法，这种分析，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.开发完全匹配和错配寡核苷酸探针对mRNA浓度变化的反应的完整建模方法，并利用此类模型构建改进表达指数的估计值。通过这样做，我们希望将估计的线性扩展到低信号范围，其中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。目标二。开发适用于相应样本预期表现出非常不同的表达模式的情况的阵列到阵列归一化方法。目标3。建立用于酵母突变体混合物研究的标记探针阵列的统计分析方法。目标4。开发基于上述方法的计算机程序模块，并将其纳入软件dChip中，以扩展其功能，用于基于模型的寡核苷酸阵列数据分析。我们还将与实验组密切合作，分析真实的数据，以确保我们的研究结果与用户群体的需求相关。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我们小组和我们的合作者开发的其他有用的分析方法并将其纳入dChip框架。目标5。与基于R的生物信息学联盟合作，以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。

项目成果

期刊论文数量（26）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Model-based analysis of oligonucleotide arrays: expression index computation and outlier detection.

DOI：
10.1073/pnas.98.1.31
发表时间：
2001-01
期刊：
Proceedings of the National Academy of Sciences of the United States of America
影响因子：
11.1
作者：
Cheng Li;W. Wong
通讯作者：
Cheng Li;W. Wong

Comparative analysis of gene sets in the Gene Ontology space under the multiple hypothesis testing framework.

多重假设检验框架下基因本体空间中基因集的比较分析。