MetaboCensoR: A Shiny Application for Data Filtering in Untargeted LC-MS Metabolomics to Enhance Interpretability

MetaboCensoR reduces feature redundancy by up to 50% in untargeted LC-MS metabolomics, significantly enhancing data interpretability across diverse biological samples.

• Why it matters: Untargeted LC-MS datasets often contain non-informative features that hinder meaningful analysis and obscure biological insights, creating a critical need for effective data filtering tools.
• What they did: MetaboCensoR is a Shiny app and R package that employs four modules—blank, redundant ion, quality-control, and peak filtering—to systematically refine peak tables, with interactive threshold optimization and annotation export.
• The result: Applying MetaboCensoR across plant, human, and bacterial datasets improved molecular network clarity, pathway analysis, and differential testing, enabling more accurate biological interpretations.