Diane Jofuku Okamuro
DBI Division of Biological Infrastructure
BIO Directorate for Biological Sciences
Start Date:
October 1, 2002
Expires:
September 30, 2007 (Estimated)
Awarded Amount to Date:
$2298924
Investigator(s):
David Allison dallison@ms.soph.uab.edu (Principal Investigator)
Stephen Barnes (Co-Principal Investigator) Grier Page (Co-Principal Investigator)
Sponsor:
University of Alabama at Birmingham
AB 1170
Birmingham, AL 35294 205/934-5266
NSF Program(s):
PLANT GENOME RESEARCH PROJECT
Field Application(s):
Program Reference Code(s):
BIOT, 9150, 9109, 1228
Program Element Code(s):
1329
ABSTRACT
Microarrays are a powerful new technology offering plant biologists the opportunity the measure the
expression of thousands of genes simultaneously. This potentially allows plant biologists to make major leaps
forward by increasing the number of factors they can examine and offering the opportunity to study the
complex relations and physiological coordination among entire genomes. For this technology to achieve its
potential, a richer understanding of the statistical properties of the data produced and statistically sound
methods for analyzing those data must be developed and made available. Unfortunately, many statistical
procedures currently used in microarray research do not have a sound statistical foundation.
This research will contribute novel statistical techniques to the microarray field that are, in all cases, rigorously validated by either mathematical proofs or computer simulations. Methods will be developed in three areas:
Measurement & Estimation, Design, & Inference. Methods will be tested on real and simulated data. Software
for all methods developed will be publicly available. A plan to educate and inform students, plant biologists
and statisticians about the methods will be implemented including a short course held at a National plant
biology meeting in year 4. The investigative team includes a cadre of investigators with track records in
organizing large collaborative efforts, developing novel statistical techniques, and disseminating methods
through educational activities and quality software. The investigative team is complemented by a blue-ribbon
panel Advisory Committee with expertise in plant biology, microarrays, and computer science.
Historically, plants of economic importance (e.g., maize, soy, wheat, pine) have been critical to our country's prosperity and growth. Today, America's strength in supplying food of high nutritional value for human and livestock consumption, cash crops for sale and export, and plant materials for construction remains critical.
Indeed, as the world population grows, the ability to produce plants for nutrition and construction materials
with tightening resources in a broadening range of environments will be essential. Given their potential to
rapidly advance understanding of basic plant biology, microarrays can enhance the ability to produce plants
with increased efficiency and enhanced characteristics in the greatest range of environments. Developing
valid techniques and facilitating use via quality software and systematic dissemination and educational
activities as will be done here can have greatly amplified impact by providing tools of use to the more than
100 other NSF-funded microarray grants and the vast ongoing microarray research world-wide.
PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH
? Brand JPL, Chen L, Cui X, Beasley TM, Page GP, Bartolucci AA, Kim K, Barnes S, Srinivasasainagendra V, Allison DB. "An adaptive alpha spending algorithm improves the power of statistical inference in microarray data analysis," Bioinformatics, v.1(10), 2007, p. 384.
? Trivedi P, Page GP, Edwards JW, Wang J, Gadbury GL, Srinivasasainagendra V, Kim K, Mehta T, Zakharkin SO, Brand JPL, Patki A, , Allison DB*. "HDBStat! : A platform-independent software suite for statistical analysis of high dimensional biology data.," BMC Bioinformatics, v.23, 1, p. 55.
Allison, D. B. & Coffey, C. S. "Two Stage Testing in Microarray Analysis: What is Gained?," Journal of Gerontology: Biological Sciences, v.57, 2002, p. b189.
Allison, D. B., Gadbury, G. L., Heo, M., Fernßndez, J., Lee, K-C., Prolla, T. A, & Weindruch, R.. "A Mixture Model Approach for the Analysis of Microarray Gene Expression Data.," Computational Statistics & Data Analysis,, v.39, 2002, p. 1.
Allison, DB; Cui, XQ; Page, CP; Sabripour, M. "Microarray data analysis: from disarray to consolidation and consensus (vol 7, pg 55, 2006)," NATURE REVIEWS GENETICS, v.7, 2006, p. 406-406.
Beasley, TM, Page GP, Brand JP, Gadbury GL, Allison DB. "ChebyshevÆs Inequality for Non-parametric Testing with Small N and a in Microarray Research," Journal of Royal Statistical Society, Series C (Applied Statistics), v.53, 2004, p. 95.
Beasley, TM; Page, GR; Brand, JPL. "Chebyshev's inequality for nonparametric testing with small N and alpha in microarray research," JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES C-APPLIED STATISTICS, v.53, 2004, p. 95-108.
Cheung, K-H, White, K., Hager, J., Gerstein, M., Reinke, V., Nelson, K., Masiar, P., Srivastava, R., Li, Y., Li, J., Zhao, H., Li, J., Allison, D.B., Snyder, M., Miller, P., & Williams, K. "YMD: A Microarray Database for Large-Scale Gene Expression Analysis," Proc AMIA Symp., v.2002, 200, p. 140.
Comparison of linear weighting-schemes for perfect match and mismatch gene expression levels from microarray data. "Comparison of linear weighting-schemes for perfect match and mismatch gene expression levels from microarray data," Am J Pharmacogenomics, v.5(3), 2005, p. 197.
Cui X, Loraine A. "Global correlation analysis between redundant probe sets using a large collection of Arabidopsis ath1 expression profiling data," Comput Syst Bioinformatics Conf, 2006, p. 223.
Dongyan Yang , Stanislav O. Zakharkin, Grier P. Page, Jacob. P. L. Brand, Jode W. Edwards, Alfred A. Bartolucci, David B. Allison. "Applications of Bayesian Statistical Methods in Microarray Data Analysis," American Journal of Pharmacogenomics, v.4, 2004, p. 53.
Edwards JW, Page GP, Gadbury G, Heo M, Kayo T, Weindruch R, Allison DB. "Empirical Bayes estimation of gene-specific effects in micro-array research," Funct Integr Genomics, v.5, 2005, p. 32.
Edwards JW, Page GP, Gadbury G, Heo M, Kayo T, Weindruch R, Allison DB. "Empirical Bayes estimation of gene-specific effects in micro-array research," Funct Integr Genomics, v.5(1), 2005, p. 32.
Gadbury GL, Page GP, Edwards JW , Kayo T, Prolla TA, Weindruch R, Permana PA, Mountz J, Allison DB. "Power and Sample Size Estimation in High Dimensional Biology," Statistical Methods in Medical Research., v.13, 2004, p. 325.
Gadbury, GL, Allison DB, Page GP, Heo M, Mountz J. "Randomization Tests for Small Samples: an Application for Genetic Expression Data," Journal of Royal Statistical Society ûC, v.52, 2003, p. 365.
Garge N, Sprague, A, Page GP, Allison DB. "Stability of non-hierarchical cluster analysis techniques," BMC Bioinformatics, v.6(2), 2006, p. S10.
Kim, K, Page GP, Beasley, TM, Barnes SB, Allison DB. "A proposed metric for assessing the measurement quality of individuals microarrays," BMC Bioinformatics, v.7, 2006, p. 35.
Mehat T, Tanik M, Allison. "Towards sound epistemological foundations of statistical methods for high-dimensional biology," Nat Genet, v.36, 2004, p. 943.
Mirisliglu M, Page GP, Sagirkaya H, Kaya A, Parrish JJ, First NL, Memilli E. "Dynamics of global transcriptome in bovine matured oocytes and preimplantation embryos," PNAS, v.103(50), 2006, p. 18905.
Page GP, Edward JE, Wang J, Yelisetti P, Trivedi P Allison DB. "The PowerAtlas: a power and sample size atlas for microarray experimental design and research.," BMC Bioinformatics, v.22(7), 2006, p. 84.
Page GP, Edwards JW, Barnes S, Weindruch R, Allison DB. "A Design and
Statistical Perspective on Microarray Gene Expression Studies in Nutrition: The Need for Playful Creativity and Scientific Hard-Mindedness," Nutrition, v.19, 2003, p. 997.
Persson S, Wei H, Milne J, Page GP, Somerville C. "Large-scale co-expression analysis reveals novel genes involved in cellulose biosynthesis.," Proc. Natl. Acad. Sci. USA., v.June, 2005.
Trivedi P, Page GP, Edwards JW, Wang J, Gadbury GL, Srinivasasainagendra V, Kim K, Mehta T, Zakharkin SO, Brand JPL, Patki A, Allison DB. "HDBStat! : A platform-independent software suite for statistical analysis of high dimensional biology data.," BMC Bioinformatics, v.6(6), 2005, p. 86.
Trivedi, P; Edwards, JW; Wang, JL; Gadbury, GL; Srinivasasainagendra, V; Zakharkin, SO; Kim, K; Mehta, T; Brand, JPL; Patki, A; Page, GP; Allison, DB. "HDBStat!: A platform-independent software suite for statistical analysis of high dimensional biology data," BMC BIOINFORMATICS, v.6, 2005.
Wei H, Perssson S, Mehta T, Srinivasasainagendra V, Chen L, Page GP, Somerville C, Loraine A.. "Transcriptional coordination of the metabolic network in Arabidopsis thaliana.," Plant Physiol., v.August, 2006.
Yang D, Zakharkin SO, Page GP, Brand JPL, Edwards JW, Bartolucci A, Allison DB. "Applications of Bayesian Statistical Methods in Microarray Data Analysis," Am. J. Pharmacogenomics, v.41(1), 2004, p. 53.
