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Grant Details

Grant Number: 5R01CA074841-09 Interpret this number
Primary Investigator: Kooperberg, Charles
Organization: Fred Hutchinson Cancer Research Center
Project Title: Adaptive Function Estimation for Genomic Data
Fiscal Year: 2006
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DESCRIPTION (provided by applicant): The publication of the sequence of the human genome and breakthroughs in the high throughput technologies for single nucleotide polymorphism (SNP) genotyping, gene expression, and protein measurements have offered new opportunities for the study of genome complexity. New technologies are generating large amounts of high dimensional data at an astounding speed. Relative to the high dimension of the data the number of independent samples is often rather small, either because the techniques are too expensive, or because it is hard to obtain enough independent biological samples. Clearly, the development of new statistical techniques is required for the extraction of useful biological information from such data. Adaptive regression methods, which combine variable selection and nonlinear modeling, are well suited for many of these problems. The aim of this proposal is to develop and enhance these methods to address the practical problems that arise directly from several collaborative projects. In particular we focus on association studies with SNP and microarray data. For SNP association studies we plan to make use of Logic Regression. This methodology combines mostly binary predictors using rules of Boolean algebra. The proposed developments include new techniques to deal with haplotype data, new approaches to model selection that scale up to high-dimensional problems, and computational techniques that make it feasible to deal with large data sets. For the analysis of microarray association studies we plan to use polynomial splines, an approach that combines nonlinear functions of predictors and low-order interactions. Gene expression measurements usually have a large variance, and measurements for different genes are often highly correlated. This, combined with the high dimensionality, makes regularization a necessity. Therefore, another focus of this proposal is to develop methods for combining predictors or models to regularize the model selection process. In addition, we plan to develop methods to improve inference for polynomial spline methodologies.

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Risk prediction using genome-wide association studies.
Authors: Kooperberg C. , LeBlanc M. , Obenchain V. .
Source: Genetic Epidemiology, 2010 Nov; 34(7), p. 643-52.
PMID: 20842684
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SHARE: an adaptive algorithm to select the most informative set of SNPs for candidate genetic association.
Authors: Dai J.Y. , Leblanc M. , Smith N.L. , Psaty B. , Kooperberg C. .
Source: Biostatistics (oxford, England), 2009 Oct; 10(4), p. 680-93.
PMID: 19605740
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Expression profiling of Huntington's disease models suggests that brain-derived neurotrophic factor depletion plays a major role in striatal degeneration.
Authors: Strand A.D. , Baquet Z.C. , Aragaki A.K. , Holmans P. , Yang L. , Cleren C. , Beal M.F. , Jones L. , Kooperberg C. , Olson J.M. , et al. .
Source: The Journal Of Neuroscience : The Official Journal Of The Society For Neuroscience, 2007-10-24 00:00:00.0; 27(43), p. 11758-68.
PMID: 17959817
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Renin-angiotensin system haplotypes and the risk of myocardial infarction and stroke in pharmacologically treated hypertensive patients.
Authors: Marciante K.D. , Bis J.C. , Rieder M.J. , Reiner A.P. , Lumley T. , Monks S.A. , Kooperberg C. , Carlson C. , Heckbert S.R. , Psaty B.M. .
Source: American Journal Of Epidemiology, 2007-07-01 00:00:00.0; 166(1), p. 19-27.
EPub date: 2007-07-01 00:00:00.0.
PMID: 17522061
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Conservation of regional gene expression in mouse and human brain.
Authors: Strand A.D. , Aragaki A.K. , Baquet Z.C. , Hodges A. , Cunningham P. , Holmans P. , Jones K.R. , Jones L. , Kooperberg C. , Olson J.M. .
Source: Plos Genetics, 2007-04-20 00:00:00.0; 3(4), p. e59.
PMID: 17447843
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Logic regression for analysis of the association between genetic variation in the renin-angiotensin system and myocardial infarction or stroke.
Authors: Kooperberg C. , Bis J.C. , Marciante K.D. , Heckbert S.R. , Lumley T. , Psaty B.M. .
Source: American Journal Of Epidemiology, 2007-02-01 00:00:00.0; 165(3), p. 334-43.
EPub date: 2007-02-01 00:00:00.0.
PMID: 17082497
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Regional and cellular gene expression changes in human Huntington's disease brain.
Authors: Hodges A. , Strand A.D. , Aragaki A.K. , Kuhn A. , Sengstag T. , Hughes G. , Elliston L.A. , Hartog C. , Goldstein D.R. , Thu D. , et al. .
Source: Human Molecular Genetics, 2006-03-15 00:00:00.0; 15(6), p. 965-77.
EPub date: 2006-03-15 00:00:00.0.
PMID: 16467349
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Global and gene-specific analyses show distinct roles for Myod and Myog at a common set of promoters.
Authors: Cao Y. , Kumar R.M. , Penn B.H. , Berkes C.A. , Kooperberg C. , Boyer L.A. , Young R.A. , Tapscott S.J. .
Source: The Embo Journal, 2006-02-08 00:00:00.0; 25(3), p. 502-11.
EPub date: 2006-02-08 00:00:00.0.
PMID: 16437161
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Prostate-specific antigen and free prostate-specific antigen in the early detection of prostate cancer: do combination tests improve detection?
Authors: Etzioni R. , Falcon S. , Gann P.H. , Kooperberg C.L. , Penson D.F. , Stampfer M.J. .
Source: Cancer Epidemiology, Biomarkers & Prevention : A Publication Of The American Association For Cancer Research, Cosponsored By The American Society Of Preventive Oncology, 2004 Oct; 13(10), p. 1640-5.
PMID: 15466981
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The histone modification pattern of active genes revealed through genome-wide chromatin analysis of a higher eukaryote.
Authors: Schübeler D. , MacAlpine D.M. , Scalzo D. , Wirbelauer C. , Kooperberg C. , van Leeuwen F. , Gottschling D.E. , O'Neill L.P. , Turner B.M. , Delrow J. , et al. .
Source: Genes & Development, 2004-06-01 00:00:00.0; 18(11), p. 1263-71.
PMID: 15175259
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Combining biomarkers to detect disease with application to prostate cancer.
Authors: Etzioni R. , Kooperberg C. , Pepe M. , Smith R. , Gann P.H. .
Source: Biostatistics (oxford, England), 2003 Oct; 4(4), p. 523-38.
PMID: 14557109
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Directed indices for exploring gene expression data.
Authors: LeBlanc M. , Kooperberg C. , Grogan T.M. , Miller T.P. .
Source: Bioinformatics (oxford, England), 2003-04-12 00:00:00.0; 19(6), p. 686-93.
PMID: 12691980
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Yeast Isw1p forms two separable complexes in vivo.
Authors: Vary J.C. , Gangaraju V.K. , Qin J. , Landel C.C. , Kooperberg C. , Bartholomew B. , Tsukiyama T. .
Source: Molecular And Cellular Biology, 2003 Jan; 23(1), p. 80-91.
PMID: 12482963
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Estimating the statistical significance of gene expression changes observed with oligonucleotide arrays.
Authors: Strand A.D. , Olson J.M. , Kooperberg C. .
Source: Human Molecular Genetics, 2002-09-15 00:00:00.0; 11(19), p. 2207-21.
PMID: 12217949
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Widespread collaboration of Isw2 and Sin3-Rpd3 chromatin remodeling complexes in transcriptional repression.
Authors: Fazzio T.G. , Kooperberg C. , Goldmark J.P. , Neal C. , Basom R. , Delrow J. , Tsukiyama T. .
Source: Molecular And Cellular Biology, 2001 Oct; 21(19), p. 6450-60.
PMID: 11533234
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