Methodological analysis reveals efficient elimination of uninformative features in untargeted metabolomics data, highlighting improved biological discovery in complex biospecimens.
Our proposed data-adaptive filtering pipeline is intuitive and effectively removes uninformative features from untargeted metabolomics datasets. It is particularly relevant for interrogation of biological phenomena in data derived from complex matrices associated with biospecimens.
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Schiffman et al. (2019) studied this question.
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