Single sample enrichment analysis for mass spectrometry-based omics data

Abstract

In omics studies using mass spectrometry, including metabolomics, it is challenging to detect all metabolites, leading to potential biases when performing traditional enrichment analyses. In this study, we applied a single sample enrichment analysis to the metabolome data of fasting mice. This method, distinct from conventional approaches, utilizes information from both detected and undetected metabolites. It is particularly useful for omics data from mass spectrometry where it is difficult to comprehensively capture all metabolites and where there are many missing values.