DIAMetAlyzer allows automated false-discovery rate-controlled analysis for data-independent acquisition in metabolomics

Abstract

The extraction of meaningful biological knowledge from high-throughput mass spectrometry data relies on limiting false discoveries to a manageable amount. Here the authors establish an automated, false discovery rate-controlled targeted analysis workflow for data-independent acquisition that enables a robust FDR estimation improving the comparability of results in the metabolomics field.