Because of the high complexity of petroleomic-type samples, there is a need for efficient ways of visualizing and interpreting the resulting data in mass spectrometry-based petroleomics. Over the years, several graphing approaches have become widespread, yet they mostly deal with a particular subset of compounds detected within a given sample. Here, we present an alternative and complementary sample visualization method, the hexagonal class representation, based on relative abundance vs compound classes plot. The representation can be used to fingerprint a petroleomic-type sample, provide a simple means of sample comparison, as well as allow for a fast overview and detection of any compound of interest based on its elemental composition and chemical properties.
Matthias Finger, Qian Wang, Yiming Li, Varun Sharma, Konstantin Androsov, Jan Steggemann, Xin Chen, Rakesh Chawla, Matteo Galli, Jian Wang, João Miguel das Neves Duarte, Tagir Aushev, Matthias Wolf, Yi Zhang, Tian Cheng, Yixing Chen, Werner Lustermann, Andromachi Tsirou, Alexis Kalogeropoulos, Andrea Rizzi, Ioannis Papadopoulos, Paolo Ronchese, Hua Zhang, Leonardo Cristella, Siyuan Wang, Tao Huang, David Vannerom, Michele Bianco, Sebastiana Gianì, Sun Hee Kim, Davide Di Croce, Kun Shi, Abhisek Datta, Jian Zhao, Federica Legger, Gabriele Grosso, Anna Mascellani, Ji Hyun Kim, Donghyun Kim, Zheng Wang, Sanjeev Kumar, Wei Li, Yong Yang, Ajay Kumar, Ashish Sharma, Georgios Anagnostou, Joao Varela, Csaba Hajdu, Muhammad Ahmad, Ekaterina Kuznetsova, Ioannis Evangelou, Milos Dordevic, Meng Xiao, Sourav Sen, Xiao Wang, Kai Yi, Jing Li, Rajat Gupta, Hui Wang, Seungkyu Ha, Pratyush Das, Anton Petrov, Xin Sun, Valérie Scheurer, Muhammad Ansar Iqbal, Lukas Layer