hplc-py: A Python Package For Rapid Peak Quantification in Complex Chromatograms

Griffin Chure^⛧, Jonas Cremer
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Scientific Abstract

High-Performance Liquid Chromatography (HPLC) and Gas Chromatography are analytical techniques which allow for the quantitative characterization of the chemical components of mixtures. Technological advancements in sample preparation and mechanical automation have allowed HPLC to become a high-throughput tool which poses new challenges for reproducible and rapid analysis of the resulting chromatograms. Here we present hplc-py, a Python package that permits rapid and reliable quantitation of component signals within a chromatogram for pipelined workflows. This is achieved by a signal detection and quantitation algorithm which i) identifies windows of time which contain peaks and ii) infers the parameters of a mixture of amplitude-weighted skew-normal distributions which sum to reconstruct the observed signal. This approach is particularly effective at deconvolving highly overlapping signals, allowing for precise absolute quantitation of chemical constituents with similar chromatographic retention times

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