Computational workflow to study the seasonal variation of secondary metabolites in nine different bryophytes

In Eco-Metabolomics, non-model organisms are typically studied in their natural environment and relations are made between biochemistry and ecological function. Current challenges when processing such data involve, among others, complex ecological experiment designs, peak detection parameter settings and high variation of metabolite profiles of different species. Here, we present a representative dataset generated from 108 samples of 9 bryophyte species obtained in four seasons using an untargeted liquid chromatography coupled with mass spectrometry (LC/MS) acquisition method. With this dataset, we address the challenges in data processing focusing on data import, analytical quality control and peak detection. We expect that this representative dataset will encourage researchers to conduct subsequent Eco-Metabolomics studies.