Abstract
Data from untargeted metabolomics studies employing nuclear magnetic resonance (NMR) spectroscopy oftentimes contain negative values. These negative values hamper data processing and analysis algorithms and prevent the use of such data in multiomics integration settings. New methods to deal with such negative values are thus an urgent need in the metabolomics community. This study presents affine transformation of negative values (ATNV), a novel algorithm for replacement of negative values in NMR data sets. ATNV was implemented in the R package mrbin, which features interactive menus for user-friendly application and is available for free for various operating systems within the free R statistical programming language. The novel algorithms were tested on a set of human urinary NMR spectra and were able to successfully identify relevant metabolites.
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