NormalizeMets: 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) <doi:10.1021/ac502439y>).

Package details

AuthorAlysha M De Livera, Gavriel Olshansky
MaintainerAlysha M De Livera <[email protected]>
LicenseGPL (>= 2)
Package repositoryView on CRAN
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NormalizeMets documentation built on May 1, 2019, 10:26 p.m.