PeakClimber: A software tool for analyzing biological HPLC data using the exponential Gaussian function

Abstract

High-performance liquid chromatography (HPLC) is a common medium-throughput technique to analyze metabolic samples. However, analysis of HPLC data is hampered by a lack of tools to accurately determine the precise analyte quantities on a level of precision equivalent to mass-spectrometry approaches. To combat this problem, we developed a tool we call PeakClimber, that uses a sum of exponential Gaussian functions to accurately quantify the peaks in HPLC traces. In this paper we analytically show that HPLC peaks are well-fit by an exponential Gaussian function, that PeakClimber more accurately quantifies known peak areas than standard industry software and utilize PeakClimber to make new discoveries about lipid biology.