Bucket Fuser: Statistical Signal Extraction for 1D ¹H NMR Metabolomic Data.

ABSTRACT: Untargeted metabolomics is a promising tool for identifying novel disease biomarkers and unraveling underlying pathomechanisms. Nuclear magnetic resonance (NMR) spectroscopy is particularly suited for large-scale untargeted metabolomics studies due to its high reproducibility and cost effectiveness. Here, one-dimensional (1D) ¹H NMR experiments offer good sensitivity at reasonable measurement times. Their subsequent data analysis requires sophisticated data preprocessing steps, including the extraction of NMR features corresponding to specific metabolites. We developed a novel 1D NMR feature extraction procedure, called Bucket Fuser (BF), which is based on a regularized regression framework with fused group LASSO terms. The performance of the BF procedure was demonstrated using

SUBMITTER: Altenbuchinger M 

PROVIDER: S-EPMC9501206 | biostudies-literature | 2022 Aug

REPOSITORIES: biostudies-literature