Data di Pubblicazione:
2013
Citazione:
muma, An R Package for Metabolomics Univariate and Multivariate Statistical Analysis / E. Gaude, F. Chignola, D. Spiliotopoulos, A. Spitaleri, M. Ghitti, J. M Garcia-Manteiga, S. Mari, G. Musco. - In: CURRENT METABOLOMICS. - ISSN 2213-2368. - 1:2(2013), pp. 180-189. [10.2174/2213235X11301020005]
Abstract:
Metabolomics, similarly to other high-throughput “-omics” techniques, generates large arrays of data, whose
analysis and interpretation can be difficult and not always straightforward. Several software for the detailed metabolomics
statistical analysis are available, however there is a lack of simple protocols guiding the user through a standard statistical
analysis of the data.
Herein we present “muma”, an R package providing a simple step-wise pipeline for metabolomics univariate and multi-
variate statistical analyses. Based on published statistical algorithms and techniques, muma provides user-friendly tools
for the whole process of data analysis, ranging from data imputation and preprocessing, to dataset exploration, to data in-
terpretation through unsupervised/supervised multivariate and/or univariate techniques. Of note, specific tools and graph-
ics aiding the explanation of statistical outcomes have been developed. Finally, a section dedicated to metabolomics data
interpretation has been implemented, providing specific techniques for molecular assignments and biochemical interpreta-
tion of metabolic patterns.
muma is a free, user-friendly and versatile tool suite tailored to assist the user in the interpretation of metabolomics data in
the identification of biomarkers and in the analysis of metabolic patterns
Tipologia IRIS:
01 - Articolo su periodico
Keywords:
Chemometrics; metabonomics; metabolic pattern; multivariate analysis; R package; statistical analysis; univariate analysis
Elenco autori:
E. Gaude, F. Chignola, D. Spiliotopoulos, A. Spitaleri, M. Ghitti, J. M Garcia-Manteiga, S. Mari, G. Musco
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