Computer Science Department Events
There will be a Colloquium on Friday October 12 at 10:30 AM by Tieming Ji
Friday, October 12, 2012 E&CS Building Auditorium (1st Floor)TIME: 10:30 AMTITLE: Borrowing information across genes and experiments for improved error variance estimation in microarray data analysis.SPEAKER: Tieming JiAbstract:
Statistical inference for microarray experiments usually involves the estimation of error variance for each gene. Because the sample size available for each gene is often low, the usual unbiased estimator of the error variance can be unreliable. Shrinkage methods, including empirical Bayes approaches that borrow information across genes to produce more stable estimates, have been developed in recent years. Because the same microarray platform is often used for at least several experiments to study similar biological systems, there is an opportunity to improve variance estimation further by borrowing information not only across genes but also across experiments. We propose a lognormal model for error variances that involves random gene effects and random experiment effects. Based on the model, we develop an empirical Bayes estimator of the error variance for each combination of gene and experiment and call this estimator BAGE because information is Borrowed Across Genes and Experiments. A permutation strategy is used to make inference about the differential expression status of each gene. Simulation studies with data generated from different probability models and real microarray data show that our method outperforms existing approaches.
Bio:
Assistant Professor at the department of statistics, University of Missouri, Columbia. I got Ph.D. from Iowa State University, and Master from New Mexico State University. My master advisor is Dr. Desh Ranjan. My research interest is statistical genomics, statistical analysis of biological experiments and bioinformatics.
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