title: How to distinguish healthy from diseased? Classification strategy for mass spectrometry-based clinical proteomics.
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 X-omics 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.
authors: ABC Metabolomics Centre, University of Utrecht, Utrecht, The Netherlands. m.hendriks-9@umcutrecht.nl
authors: Margriet M W B
authors: MM
authors: Hendriks
authors: Suzanne
authors: S
authors: Smit
authors: Wies L M W
authors: WL
authors: Akkermans
authors: Theo H
authors: TH
authors: Reijmers
authors: Paul H C
authors: PH
authors: Eilers
authors: Huub C J
authors: HC
authors: Hoefsloot
authors: Carina M
authors: CM
authors: Rubingh
authors: Chris G
authors: CG
authors: de Koster
authors: Johannes M
authors: JM
authors: Aerts
authors: Age K
authors: AK
authors: Smilde
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D015415:Biomarkers / Q000032:analysis / Q000097:blood; D001798:Blood Proteins / Q000032:analysis* / Q000145:classification* / Q000378:metabolism; D005260:Female; D005776:Gaucher Disease / Q000097:blood / Q000145:classification / Q000175:diagnosis; D006801:Humans; D008297:Male; D008875:Middle Aged; D040901:Proteomics / Q000379:methods*; D019032:Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization / Q000379:methods / Q000706:statistics & numerical data
chemical_list: D015415:Biomarkers; D001798:Blood Proteins