A data object of class
consisting of 654 mass spectra (327 spectra in duplicate) from 2000 to
20000 Da, which were generated from patients with prostate cancer,
benign prostatic hypertrophy, and normal controls. These spectra are
already baseline corrected and normalized. Please see the references for
Since the original package msProstate is orphaned at the end of 2012, the data are included in the ChemometricsWithR package so that the examples in the book are still executable. This manual page has been adapted to reflect this.
B.L. Adam, Y. Qu, J.W. Davis, M.D. Ward, M.A. Clements, L.H. Cazares, O.J. Semmes, P.F. Schellhammer, Y. Yasui, Z. Feng, and G.L. Wright, Jr., "Serum protein fingerprinting coupled with a pattern-matching algorithm distinguishes prostate cancer from benign prostate hyperplasia and healthy men," Cancer Research, 62(13):3609–14, 2002.
Y. Qu, B.L. Adam, Y. Yasui, M.D. Ward, L.H. Cazares, P.F. Schellhammer, Z. Feng, O.J. Semmes, and G.L. Wright Jr., "Boosted decision tree analysis of surface-enhanced laser desorption/ionization mass spectral serum profiles discriminates prostate cancer from noncancer patients", Clinical Chemistry, 48(10):1835–43, 2002.
R. Wehrens, "Chemometrics with R - Multivariate Data Analysis in the Natural Sciences and Life Sciences". Springer, Heidelberg, 2011.
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## Examples have been changed from the original man page upon inclusion ## in the ChemometricsWithRData package data("Prostate2000Raw") ## plot a few spectra, partially matplot(Prostate2000Raw$mz[1:8000], Prostate2000Raw$intensity[1:8000, 1:5], type = "l", lty = 1, col = 1:5, xlab = "m/z", ylab = "response")
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