MetNorm: Statistical Methods for Normalizing 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 contains a collection of R functions which can be used to remove unwanted variation and obtain normalized metabolomics data.
||Alysha M De Livera
||Alysha M De Livera <alyshad at unimelb.edu.au>
||GPL-2 | GPL-3
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