title: Data reduction using a discrete wavelet transform in discriminant analysis of very high dimensionality data.
abstract: We present a method of data reduction using a wavelet transform in discriminant analysis when the number of variables is much greater than the number of observations. The method is illustrated with a prostate cancer study, where the sample size is 248, and the number of variables is 48,538 (generated using the ProteinChip technology). Using a discrete wavelet transform, the 48,538 data points are represented by 1271 wavelet coefficients. Information criteria identified 11 of the 1271 wavelet coefficients with the highest discriminatory power. The linear classifier with the 11 wavelet coefficients detected prostate cancer in a separate test set with a sensitivity of 97% and specificity of 100%.
authors.affiliation: Cancer Prevention Research Program, Fred Hutchinson Cancer Research Center, 1100 Fairview Ave. N. MP-702 Seattle, Washington, USA. yqu@fhcrc.org
authors.forename: Yinsheng
authors.initials: Y
authors.lastname: Qu
authors.forename: Bao-Ling
authors.initials: BL
authors.lastname: Adam
authors.forename: Mark
authors.initials: M
authors.lastname: Thornquist
authors.forename: John D
authors.initials: JD
authors.lastname: Potter
authors.forename: Mary Lou
authors.initials: ML
authors.lastname: Thompson
authors.forename: Yutaka
authors.initials: Y
authors.lastname: Yasui
authors.forename: John
authors.initials: J
authors.lastname: Davis
authors.forename: Paul F
authors.initials: PF
authors.lastname: Schellhammer
authors.forename: Lisa
authors.initials: L
authors.lastname: Cazares
authors.forename: MaryAnn
authors.initials: M
authors.lastname: Clements
authors.forename: George L
authors.initials: GL
authors.lastname: Wright
authors.forename: Ziding
authors.initials: Z
authors.lastname: Feng
mesh_terms: D044962:Data Compression / Q000379:methods*; D016002:Discriminant Analysis; D006801:Humans; D008297:Male; D013058:Mass Spectrometry / Q000706:statistics & numerical data; D025341:Principal Component Analysis; D011471:Prostatic Neoplasms / Q000175:diagnosis