Open-source Python module to automate GC-MS data analysis developed in the context of bio-oil analyses

Abstract

GC-MS (Gas Chromatography-Mass Spectrometry) is widely used to measure the composition of biofuels and complex organic mixtures. However, the proprietary GC-MS software associated with each instrument is often clunky and cannot quantify compounds based on similarity indices. Beyond slowing individual research group's efforts, the lack of universal free software to automatically process GC-MS data hampers field-wide efforts to improve bio-oil processes as data are often not comparable across research groups. We developed “gcms_data_analysis,” an open-source Python tool that automatically: (1) handles multiple GCMS semi-quantitative data tables (whether derivatized or not), (2) builds a database of all identified compounds and relevant properties using PubChemPy, (3) splits each compound into its functional groups using a published fragmentation algorithm, (4) applies calibrations and/or semi-calibration using Tanimoto and molecular weight similarities, and (5) produces multiple different reports, including one based on functional group mass fractions in the samples. The module is available on PyPI (https://pypi.org/project/gcms-data-analysis/) and on GitHub (https://github.com/mpecchi/gcms_data_analysis).