Chroma: A MATLAB package and open-source platform for biomarker data processing and automatic index calculations

Abstract

The molecular ratio indices of biological markers (biomarkers), such as the Carbon Preference Index (CPI) or P_aq, are frequently used as proxies for paleoclimatic and palaeoecological conditions. These indices are regularly extracted from the relative abundances of target molecules detected by a Gas Chromatography analyzer with a Flame Ionization Detector (GC-FID). Despite their use in biogeochemical studies for over a half-century, it remains common procedure to quantify the abundance of individual compounds by manual integration of chromatogram peaks (i.e., interpret baselines visually and characterize peaks by hand), which is time consuming and can lead to inconsistent results. Here, we introduce a new MATLAB package (Chroma) for the automatic detection and integration of standard-referenced biomarker abundances and the calculation of a variety of established hydrocarbon indices commonly reported in the published literature. The algorithm identifies the detector response timing of specific target peaks in a sample chromatogram by cross-referencing to a standard (e.g., Mix-A6, Schimmelmann, Indiana University Bloomington), then calculates the peak areas for an approximation of molecular abundance. This new toolkit for automatic and rapid integration of GC-acquired data provides a consistent and reproducible approach for the calculation of hydrocarbon indices and offers a standardized inter-laboratory platform for data comparisons and exchange. We validate the utility of the Chroma package with the chromatograms of plant wax n-alkanes, a widely used proxy for ecology and hydrology, from six stratigraphic sections in the Tibetan Plateau. Chroma is an effective tool for efficient data processing and will continuously evolve to accommodate extended uses in related areas of biomarker research beyond n-alkanes.