SRV: an open-source toolbox to accelerate the recovery of metabolic biomarkers and correlations from metabolic phenotyping datasets.
Bioinformatics
; 29(10): 1348-9, 2013 May 15.
Article
en En
| MEDLINE
| ID: mdl-23508967
ABSTRACT
MOTIVATION Supervised multivariate statistical analyses are often required to analyze the high-density spectral information in metabolic datasets acquired from complex mixtures in metabolic phenotyping studies. Here we present an implementation of the SRV-Statistical Recoupling of Variables-algorithm as an open-source Matlab and GNU Octave toolbox. SRV allows the identification of similarity between consecutive variables resulting from the high-resolution bucketing. Similar variables are gathered to restore the spectral dependency within the datasets and identify metabolic NMR signals. The correlation and significance of these new NMR variables for a given effect under study can then be measured and represented on a loading plot to allow a visual and efficient identification of candidate biomarkers. Further on, correlations between these candidate biomarkers can be visualized on a two-dimensional pseudospectrum, representing a correlation map, helping to understand the modifications of the underlying metabolic network. AVAILABILITY:
SRV toolbox is encoded in MATLAB R2008A (Mathworks, Natick, MA) and in GNU Octave. It is available free of charge at http//www.prabi.fr/redmine/projects/srv/repository with a tutorial. CONTACT benjamin.blaise@chu-lyon.fr or vincent.navratil@univ-lyon1.fr.
Texto completo:
1
Banco de datos:
MEDLINE
Asunto principal:
Algoritmos
/
Programas Informáticos
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Biomarcadores
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Análisis Multivariante
Tipo de estudio:
Prognostic_studies
Límite:
Humans
Idioma:
En
Revista:
Bioinformatics
Asunto de la revista:
INFORMATICA MEDICA
Año:
2013
Tipo del documento:
Article
País de afiliación:
Francia