期刊
ANALYTICAL BIOCHEMISTRY
卷 433, 期 2, 页码 102-104出版社
ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.ab.2012.10.011
关键词
PCA; PLS-DA; MVA; UPGMA; Metabolomics
资金
- National Institutes of Health [RO1 AI087668, R21 AI087561]
- NIH National Center for Research Resources [P20 RR-17675]
- America Heart Association [0860033Z]
- Nebraska Research Council
Metabolic fingerprinting studies rely on interpretations drawn from low-dimensional representations of spectral data generated by methods of multivariate analysis such as principal components analysis and projection to latent structures discriminant analysis. The growth of metabolic fingerprinting and chemometric analyses involving these low-dimensional scores plots necessitates the use of quantitative statistical measures to describe significant differences between experimental groups. Our updated version of the PCAtoTree software provides methods to reliably visualize and quantify separations in scores plots through dendrograms employing both nonparametric and parametric hypothesis testing to assess node significance, as well as scores plots identifying 95% confidence ellipsoids for all experimental groups. (C) 2012 Elsevier Inc. All rights reserved.
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