Improved classification accuracy in 1- and 2-dimensional NMR metabolomics data using the variance stabilising generalised logarithm transformation

Classifying nuclear magnetic resonance (NMR) spectra is a crucial step in many metabolomics experiments. Since several multivariate classification techniques depend upon the variance of the data, it is important to first minimise any contribution from unwanted technical variance arising from sample...

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Veröffentlicht in:	BMC bioinformatics Jg. 8; H. 1; S. 234
Hauptverfasser:	Parsons, Helen M, Ludwig, Christian, Günther, Ulrich L, Viant, Mark R
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	England BioMed Central Ltd 02.07.2007 BioMed Central BMC
Schlagworte:	Algorithms Analysis of Variance Data Interpretation, Statistical Gene Expression Profiling - methods Health aspects Magnetic Resonance Spectroscopy - methods Metabolomics Multivariate analysis Nuclear magnetic resonance Proteome - metabolism Sensitivity and Specificity United Kingdom
ISSN:	1471-2105, 1471-2105
Online-Zugang:	Volltext
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