A data set for evaluation of peak detection methods

Nontargeted mass spectrometry (MS) has become an important method over the last years in the fields of metabolomics and environmental research. While more and more algorithms and workflows become available to process a large number of data sets nontargeted, there still exist few manually evaluated universal test data sets for refining and evaluating these methods. The first step of nontargeted screening, peak detection (and refinement of it) is arguably the most important step for nontargeted screening. However, the absence of a model data set makes it harder for researchers to evaluate peak detection methods. The data set was created from a previous real-world study, of which a subset was used to extract and manually classify ion chromatograms by three mass spectrometry experts.This data set is related to a Data Descriptor paper submitted to Metabolomics.