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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Vydané v:	BMC bioinformatics Ročník 8; číslo 1; s. 234
Hlavní autori:	Parsons, Helen M, Ludwig, Christian, Günther, Ulrich L, Viant, Mark R
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	England BioMed Central Ltd 02.07.2007 BioMed Central BMC
Predmet:	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
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