This repository contains supplementary materials relating to the manuscript "Comprehensive mass spectrometry‐guided phenotyping of plant specialized metabolites reveals metabolic diversity in the cosmopolitan plant family Rhamnaceae".
The data analysis workflow described in this paper is now available through a MolNetEhnacer module in GNPS web platform. Relevant information can be found in Metabolites 2019, 9, 144.
Jupyter notebook used to map metadata onto the mass spectral molecular network in Cytoscape version 3.4.0 (Shannon et al., 2003) for the MZmine 2 (Pluskal et al., 2010) preprocessed dataset.
The folder called ClassyFire contains R scripts and data files used for performing automated chemical classification of the in silico annotated structures using ClassyFire (Djoumbou Feunang et al., 2016).
The folder called Mass2Motifs_2_MolecularNetwork contains R scripts and data files used for mapping Mass2Motifs (Van der Hooft et al., 2016; Wandy et al., 2018) on the mass spectral molecular networks (Wang et al., 2016; Watrous et al., 2012).
The folder called ChemicalClass_DistanceMetric contains python and R scripts as well as data files used for calculating a chemically informed distance metric based on ClassyFire chemical ontology inspired by the metric proposed by Junker, 2018.
The folder called CSCD contains jupyter notebooks and data files used for calculating the chemical structural and compositional dissimilarity (CSCD) proposed by Sedio et al., 2017.