Please upload your dataThis module supports functional analysis of untargeted metabolomics data generated from high-resolution mass spectrometry (HRMS). The basic assumption is that putative annotation at individual compound level can collectively predict changes at functional levels as defined by metabolite sets or pathways. This is because changes at group level rely on "collective behavior" which is more tolerant to random errors in compound annotation as demonstrated by Li et al. To use this approach,
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