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Semi-Automated Data Analysis for Ion-Selective Electrodes and Arrays Using the R Package ISEtools.

Semi-Automated Data Analysis for Ion-Selective Electrodes and Arrays Using the R Package ISEtools. Thumbnail


Abstract

A new software package, ISEtools, is introduced for use within the popular open-source programming language R that allows Bayesian statistical data analysis techniques to be implemented in a straightforward manner. Incorporating all collected data simultaneously, this Bayesian approach naturally accommodates sensor arrays and provides improved limit of detection estimates, including providing appropriate uncertainty estimates. Utilising >1500 lines of code, ISEtools provides a set of three core functions-loadISEdata, describeISE, and analyseISE- for analysing ion-selective electrode data using the Nikolskii-Eisenman equation. The functions call, fit, and extract results from Bayesian models, automatically determining data structures, applying appropriate models, and returning results in an easily interpretable manner and with publication-ready figures. Importantly, while advanced statistical and computationally intensive methods are employed, the functions are designed to be accessible to non-specialists. Here we describe basic features of the package, demonstrated through a worked environmental application.

Citation

(2019). Semi-Automated Data Analysis for Ion-Selective Electrodes and Arrays Using the R Package ISEtools. Sensors, https://doi.org/10.3390/s19204544

Acceptance Date Oct 16, 2019
Publication Date Oct 19, 2019
Journal Sensors
Print ISSN 1424-8220
Publisher MDPI
DOI https://doi.org/10.3390/s19204544
Keywords analytical methods; Bayesian methods; calibration; electrochemistry; limit of detection
Publisher URL https://doi.org/10.3390/s19204544

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