Martin Rosmo Hansen

Abstract Feature-based molecular networking (FBMN) is a popular analysis approach for liquid chromatography–tandem mass spectrometry-based non-targeted metabolomics data. While processing liquid chromatography–tandem mass spectrometry data through FBMN is fairly streamlined, downstream data handling and statistical interrogation are often a key bottleneck. Especially users new to statistical analysis struggle to effectively handle and analyze complex data matrices.

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Pesticide residues from Denmark’s intensive-farming industry are contaminating the country’s groundwater, which is used exclusively as its source of tap water (see, for example, go.nature.com/2iumpdx). This is despite the governments’s raft of protection measures that have been in place since 1994 (see go.nature.com/2xhinf7). Pesticide residues in drinking water are a threat to public health.