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.

Agency
National Institute of Health (NIH)
Institute
National Human Genome Research Institute (NHGRI)
Type
Research Project (R01)
Project #
1R01HG002341-01
Application #
6346533
Study Section
Genome Study Section (GNM)
Program Officer
Feingold, Elise A
Project Start
2000-09-15
Project End
2003-06-30
Budget Start
2000-09-15
Budget End
2001-06-30
Support Year
1
Fiscal Year
2000
Total Cost
$373,600
Indirect Cost
Name
Harvard University
Department
Biostatistics & Other Math Sci
Type
Schools of Public Health
DUNS #
City
Boston
State
MA
Country
United States
Zip Code
02115
Xing, Yi; Stoilov, Peter; Kapur, Karen et al. (2008) MADS: a new and improved method for analysis of differential alternative splicing by exon-tiling microarrays. RNA 14:1470-9
Li, Cheng; Beroukhim, Rameen; Weir, Barbara A et al. (2008) Major copy proportion analysis of tumor samples using SNP arrays. BMC Bioinformatics 9:204
Chan, Maren M; Lu, Xin; Merchant, Faisal M et al. (2007) Serial transplantation of NMU-induced rat mammary tumors: a model of human breast cancer progression. Int J Cancer 121:474-85
Kapur, Karen; Xing, Yi; Ouyang, Zhengqing et al. (2007) Exon arrays provide accurate assessments of gene expression. Genome Biol 8:R82
Johnson, W Evan; Li, Cheng; Rabinovic, Ariel (2007) Adjusting batch effects in microarray expression data using empirical Bayes methods. Biostatistics 8:118-27
Xing, Yi; Ouyang, Zhengqing; Kapur, Karen et al. (2007) Assessing the conservation of mammalian gene expression using high-density exon arrays. Mol Biol Evol 24:1283-5
Kim, Ryung S; Ji, Hongkai; Wong, Wing H (2006) An improved distance measure between the expression profiles linking co-expression and co-regulation in mouse. BMC Bioinformatics 7:44
Beroukhim, Rameen; Lin, Ming; Park, Yuhyun et al. (2006) Inferring loss-of-heterozygosity from unpaired tumors using high-density oligonucleotide SNP arrays. PLoS Comput Biol 2:e41
Zhang, Xuegong; Lu, Xin; Shi, Qian et al. (2006) Recursive SVM feature selection and sample classification for mass-spectrometry and microarray data. BMC Bioinformatics 7:197
Hong, Pengyu; Wong, Wing H (2005) GeneNotes--a novel information management software for biologists. BMC Bioinformatics 6:20

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