Analysis of Metabolomics Data

Metabolomics data are inevitably subject to a component of unwanted variation, due to factors such as batch effects, matrix effects, and confounding biological variation. This package is a collection of functions designed to implement, assess, and choose a suitable normalization method for a given metabolomics study (De Livera et al (2015) ).


Reference manual

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0.25 by Alysha M De Livera, a year ago

Browse source code at

Authors: Alysha M De Livera , Gavriel Olshansky

Documentation:   PDF Manual  

GPL (>= 2) license

Imports impute, crmn, limma, plotly, e1071, AUC, htmlwidgets, ggplot2, GGally, grid, rmarkdown, knitr

See at CRAN