Improving Data Analysis in Chemistry and Biology Through Versatile Baseline Correction

AbstractAccurate data analysis is a cornerstone for the meaningful interpretation of measurements in chemistry and biology. To enable accurate analysis, it is often necessary to remove the background from a measurement via baseline correction, as is commonly done for spectroscopy or chromatography. However, no equivalent methods for baseline correction exist for an entire group of measurements, which includes chemical reaction measurements, quantitative polymerase chain reaction and X‐ray absorption spectroscopy. This is because these measurements give rise to a different class of features in their signals, which prevent the application of classical baseline correction methods. In this work, a general method for baseline correction of these features is developed, which is shown to simplify and improve data analysis for these measurements. Through publicly accessible and easy to use software we expect this method to be broadly useful to improve and simplify data analysis for chemists and biologists.