Exploring non-target screening variability in unsupervised multivariate time trend analysis of LC-HRMS data.

ABSTRACT: Non-target screening (NTS) using liquid chromatography-high-resolution mass spectrometry has become essential for uncovering unknown contaminants in complex matrices such as industrial wastewater. A key goal in these applications is detecting and interpreting time trends, especially spill-related events. The clarity of multivariate models depends on the quality of feature lists from various software tools. In this study, we evaluated five peak picking tools (MarkerView, MZmine3, XCMS, OpenMS, and SIRIUS) for unsupervised time trend exploration using sparse principal component analysis (SPCA). SPCA selects the most informative features per component, improving interpretability and reducing confounding variables. Two datasets were used: a controlled validation set of pooled wastewater sample

SUBMITTER: Armin R 

PROVIDER: S-EPMC12775120 | biostudies-literature | 2026 Jan

REPOSITORIES: biostudies-literature