vascr: An R-based toolkit for rapid and robust analysis of cellular impedance sensing data

Abstract

Abstract Purpose Electrical impedance sensing offers a powerful, non-invasive method for real-time monitoring of cellular behaviour, with applications spanning immunology, cancer biology and drug discovery. Adoption of impedance-sensing approaches has been accelerated by the commercial availability of the ECIS, xCELLigence, ScioSpec and cellZscope platforms; however, the complexity and volume of impedance datasets produced has limited rigorous analysis. Methods vascr, an open-source R-based toolkit designed to streamline the processing of impedance sensing datasets was created to facilitate rapid and simplified handling of cellular impedance sensing data. Results vascr can import multi-frequency data from multiple instrument manufacturers and includes robust analysis tools for resampling, outlier detection, and statistical testing using ANOVA and cross-correlation. Conclusions Using the vascr workflow, impedance sensing data can be rapidly and robustly interpreted allowing for real-time investigations of the effects of biological agents on cellular processes such as endothelial barrier integrity.