Repository hosted by TU Delft Library

Home · Contact · About · Disclaimer ·
 

How to distinguish healthy from diseased? Classification strategy for mass spectrometry-based clinical proteomics

Publication files not online:

Author: Hendriks, M.M.W.B. · Smit, S. · Akkermans, W.L.M.W. · Reijmers, T.H. · Eilers, P.H.C. · Hoefsloot, H.C.J. · Rubingh, C.M. · Koster, C.G. de · Aerts, J.M. · Smilde, A.K.
Type:article
Date:2007
Institution: TNO Kwaliteit van Leven
Source:Proteomics, 20, 7, 3672-3680
Identifier: 240209
doi: doi:10.1002/pmic.200700046
Keywords: Biology · Analytical research · Classification · Gaucher · SELDI-MS · Validation · adolescent · adult · aged · article · clinical article · controlled study · female · Gaucher disease · human · male · mass spectrometry · priority journal · proteomics · sensitivity and specificity · statistical analysis · Adolescent · Adult · Aged · Biological Markers · Blood Proteins · Female · Gaucher Disease · Humans · Male · Middle Aged · Proteomics · Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization

Abstract

SELDI-TOF-MS is rapidly gaining popularity as a screening tool for clinical applications of proteomics. Application of adequate statistical techniques in all the stages from measurement to information is obligatory. One of the statistical methods often used in proteomics is classification: the assignment of subjects to discrete categories, for example healthy or diseased. Lately, many new classification methods have been developed, often specifically for the analysis of Xomics data. For proteomics studies a good strategy for evaluating classification results is of prime importance, because usually the number of objects will be small and it would be wasteful to set aside part of these as a 'mere' test set. The present paper offers such a strategy in the form of a protocol which can be used for choosing among different statistical classification methods and obtaining figures of merit of their performance. This paper also illustrates the usefulness of proteomics in a clinical setting, serum samples from Gaucher disease patients, when used in combination with an appropriate classification method. © 2007 Wiley-VCH Verlag GmbH & Co. KGaA.