Untangling comprehensive two-dimensional liquid chromatography data sets using regions of interest and multivariate curve resolution approaches

Data analysis remains a major challenge in the global application of comprehensive two-dimensional liquid chromatography (LC × LC). Advanced chemometric tools have been proposed to reduce the complexity of LC × LC datasets. In this work, key aspects of LC × LC are summarized from a chemometrics perspective. In particular, the recently developed ROIMCR method is proposed and adapted for LC × LC data analysis. First, this strategy consists of selecting of the Regions of Interest (ROI), in which data are filtered and compressed. Second, the resolution of the elution profiles of the sample constituents using the Multivariate Curve Resolution – Alternating Least Squares (MCR-ALS) method. A detailed overview of this recently developed tool and examples of its application in LC × LC are given, as well as pre-processing and post-processing tools to facilitate and complement the analysis of LC × LC data and the optimal interpretation of results.The research leading to these results has received funding from the Spanish Ministry of Science and Innovation (MCI, Grants CTQ2017-82598-P and PID2019-105732GB-C21). The authors also want to grant support from the Catalan Agency for Management of University and Research Grants (AGAUR, Grant 2017SGR753) and the Spanish MCI (Severo Ochoa Project CEX2018-000794-S). MPC acknowledges a predoctoral FPU 16/02640 scholarship from the Spanish Ministry of Education and Vocational Training (MEFP).Peer reviewe