Imperial College London

DrTimothyEbbels

Faculty of MedicineDepartment of Metabolism, Digestion and Reproduction

Reader in Computational Bioinformatics
 
 
 
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Contact

 

+44 (0)20 7594 3160t.ebbels Website

 
 
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Location

 

131Sir Alexander Fleming BuildingSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@article{Posma:2012:10.1021/ac302360v,
author = {Posma, JM and Garcia-Perez, I and De, Iorio M and Lindon, JC and Elliott, P and Holmes, E and Ebbels, TMD and Nicholson, JK},
doi = {10.1021/ac302360v},
journal = {Analytical Chemistry},
pages = {10694--10701},
title = {Subset Optimization by Reference Matching (STORM): An optimized statistical approach for recovery of metabolic biomarker structural information from ¹H NMR spectra of biofluids},
url = {http://dx.doi.org/10.1021/ac302360v},
volume = {84},
year = {2012}
}

RIS format (EndNote, RefMan)

TY  - JOUR
AB - We describe a new multivariate statistical approach to recover metabolite structure information from multiple 1H NMR spectra in population sample sets. SubseT Optimization by Reference Matching (STORM) was developed to select subsets of 1H NMR spectra that contain specific spectroscopic signatures of biomarkers differentiating between different human populations. STORM aims to improve the visualization of structural correlations in spectroscopic data using these reduced spectral subsets containing smaller numbers of samples than the number of variables (n<<p). We have used ‘statistical shrinkage’ to limit the number of false positive associations and to simplify the overall interpretation of the auto-correlation matrix. The STORM approach has been applied to findings from an on-going human Metabolome-Wide Association study on Body Mass Index to identify a biomarker metabolite present in a subset of the population. Moreover, we have shown how STORM improves the visualization of more abundant NMR peaks compared to a previously published method (STOCSY). STORM is a useful new tool for biomarker discovery in the ‘omic’ sciences that has a widespread applicability. It can be applied to any type of data, provided that there is interpretable correlation among variables, and can also be applied to data with more than 1 dimension (e.g. 2D-NMR spectra).
AU - Posma,JM
AU - Garcia-Perez,I
AU - De,Iorio M
AU - Lindon,JC
AU - Elliott,P
AU - Holmes,E
AU - Ebbels,TMD
AU - Nicholson,JK
DO - 10.1021/ac302360v
EP - 10701
PY - 2012///
SN - 0003-2700
SP - 10694
TI - Subset Optimization by Reference Matching (STORM): An optimized statistical approach for recovery of metabolic biomarker structural information from ¹H NMR spectra of biofluids
T2 - Analytical Chemistry
UR - http://dx.doi.org/10.1021/ac302360v
UR - http://pubs.acs.org/doi/abs/10.1021/ac302360v
VL - 84
ER -