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Updated: Jul 18, 2026

Basics of Multivariate Analysis in Neuroimaging Data
Published on: July 24, 2010
Analysis and understanding of high-dimensionality data by means of multivariate data analysis
Bo Nordén1, Per Broberg, Claes Lindberg
1Department of Medicinal Chemistry, AstraZeneca R&D, S-22187 Lund. bo.norden@astrazeneca.com
Abstract:
Multivariate analysis such as principal-components analysis (PCA) and partial-least-squares-discriminant analysis (PLS-DA) have been applied to peptidomics data from clinical urine samples subjected to LC/MS analysis. We show that it is possible to use these methods to get information from a complex set of clinical data. The aim of the work is to use this information as a first step in the further search for clinical biomarker data. It is possible to identify peptide-biomarker fingerprints related to disease diagnosis and progression. Further, we review clinical proteomics and pharmacogenomics data analyzed with the same multivariate approach.
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