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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) <doi:10.1021/ac502439y>).
Package details |
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Author | Alysha M De Livera, Gavriel Olshansky |
Maintainer | Alysha M De Livera <alyshad@unimelb.edu.au> |
License | GPL (>= 2) |
Version | 0.25 |
Package repository | View on CRAN |
Installation |
Install the latest version of this package by entering the following in R:
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