JSM 2005 - Toronto

Abstract #302642

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Activity Number: 383
Type: Invited
Date/Time: Wednesday, August 10, 2005 : 10:30 AM to 12:20 PM
Sponsor: IMS
Abstract - #302642
Title: High-dimensional Analysis of Variance with Application to MALDI-TOF Mass Spectrometry in Synthetic Polymer Experiments
Author(s): Zhan-Qian J. Lu*+
Companies: National Institute of Standards and Technology
Address: 820 W. Diamond Avenue 820/353, Gaithersburg, MD, 20899-8980,
Keywords: High-dimensional statistics ; functional ANOVA ; molecular mass distribution ; Dimension reduction ; singular value decomposition ; high throughput experiments
Abstract:

Modern measurement instruments often produce high-dimensional data in the form of spectra or functional curves. There is acute need for new statistical methodology for analysis and uncertainty assessment of high-dimensional data in high-throughput experiments. This paper develops a new type of analysis of variance methodology for high-dimensional experimental data and applies it to analysis of molecular mass distribution data from MALDI-TOF mass spectrometry in synthetic polymer experiments. The statistical methodology consists of exploratory and visualization tools for functional data analysis using singular value decomposition and new developments of high-dimensional discriminant analysis for assessment of repeatability/ reproducibility of high-dimensional measurements. The proposed methodology should be useful in many other areas, such as chemical spectroscopy, microarray data analysis, and proteomics.

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Revised March 2005