These are preliminary reports that have not been peer-reviewed. They should not be regarded as conclusive, guide clinical practice/health-related behavior, or be reported in news media as established information. For more information, please see our FAQs.
romance2.pdf (921.56 kB)

A Mature ROMANCE: A Matter of Quantity and How Two Can Be Better than One

submitted on 12.05.2020, 10:06 and posted on 14.05.2020, 06:08 by Santiago Codesido, Nicolas Drouin, Sabrina Ferre, Julie Schappler, Serge Rudaz, Víctor González-Ruiz

Capillary electrophoresis coupled to mass spectrometry (CE-MS) is increasingly gaining momentum as an analytical tool in metabolomics, thanks to its ability to ob- tain information about the most polar elements in biological samples. This has been helped by improvements in peak robustness by means of mobility-scale representations of the electropherograms (mobilograms). As a necessary step towards the use of CE- MS for untargeted metabolomics data, the authors previously developed and introduced the ROMANCE software, with the purpose of automating mobilogram generation for large untargeted datasets while offering a simple and self-contained user interface. In natural continuation ROMANCE has been upgraded to its v2 to read other types of data (targeted MS data and 2D UV-like electropherograms), offer more flexibility in the transformation parameters (including field ramping delays and the use of sec- ondary markers), more measurement conditions (depending on detection and ionization modes), and most importantly tackle the issue of quantitative CE-MS. To prepare the ground for such an upgrade, we present a review of the current theoretical framework with regards to peak reproducibility and quantification, and we develop new formulas for multiple marker peak area corrections, for anticipating peak position precision, and for assessing peak shape distortion. We then present the new version of the software, and validate it experimentally. We contrast the multiple marker mobility transfor- mations with previous results, finding increased precision, and finally we showcase an application to actual untargeted metabolomics data.


Swiss National Science Foundation grant 31003A 166658

Swiss Centre for Applied Human Toxicology through grants from the Research Programme 2017-2020 (Core Project 3: Neurotoxicity)


Email Address of Submitting Author


Institute of Pharmaceutical Sciences of Western Switzerland, University of Geneva



ORCID For Submitting Author


Declaration of Conflict of Interest

The authors declare no conflict of interest

Version Notes

Version 1.0.