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Spectral relative standard deviation : a practical benchmark in metabolomics

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Parsons, Helen, Ekman, Drew R., Collette, Timothy W. and Viant, Mark R. (2009) Spectral relative standard deviation : a practical benchmark in metabolomics. The Analyst, 134 (3). pp. 478-485. doi:10.1039/b808986h ISSN 0003-2654.

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Official URL: http://dx.doi.org/10.1039/B808986H

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Abstract

Metabolomics datasets, by definition, comprise of measurements of large numbers of metabolites. Both technical (analytical) and biological factors will induce variation within these measurements that is not consistent across all metabolites. Consequently, criteria are required to assess the reproducibility of metabolomics datasets that are derived from all the detected metabolites. Here we calculate spectrum-wide relative standard deviations (RSDs; also termed coefficient of variation, CV) for ten metabolomics datasets, spanning a variety of sample types from mammals, fish, invertebrates and a cell line, and display them succinctly as boxplots. We demonstrate multiple applications of spectral RSDs for characterising technical as well as inter-individual biological variation: for optimising metabolite extractions, comparing analytical techniques, investigating matrix effects, and comparing biofluids and tissue extracts from single and multiple species for optimising experimental design. Technical variation within metabolomics datasets, recorded using one- and two-dimensional NMR and mass spectrometry, ranges from 1.6 to 20.6% (reported as the median spectral RSD). Inter-individual biological variation is typically larger, ranging from as low as 7.2% for tissue extracts from laboratory-housed rats to 58.4% for fish plasma. In addition, for some of the datasets we confirm that the spectral RSD values are largely invariant across different spectral processing methods, such as baseline correction, normalisation and binning resolution. In conclusion, we propose spectral RSDs and their median values contained herein as practical benchmarks for metabolomics studies.

Item Type: Journal Article
Divisions: Faculty of Science, Engineering and Medicine > Medicine > Warwick Medical School > Health Sciences > Cancer Research Unit
Faculty of Science, Engineering and Medicine > Medicine > Warwick Medical School > Health Sciences
Faculty of Science, Engineering and Medicine > Medicine > Warwick Medical School
Journal or Publication Title: The Analyst
Publisher: Royal Society of Chemistry
ISSN: 0003-2654
Official Date: 2009
Dates:
DateEvent
2009Published
Volume: 134
Number: 3
Page Range: pp. 478-485
DOI: 10.1039/b808986h
Status: Peer Reviewed
Publication Status: Published
Access rights to Published version: Restricted or Subscription Access

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