Oller Moreno, SergioMallafre Muro, CeliaFernández Romero, LuisCaballero, EduardoBlanco, A.Gumà, J.Marco Colás, SantiagoPardo Martínez, Antonio2024-04-122024-04-122023-10-150169-7439https://hdl.handle.net/2445/209870Gas-Chromatography coupled to Ion Mobility Spectrometry (GC-IMS) based metabolomics is an emerging technique for obtaining fast, reliable untargeted metabolic fingerprints of biofluids. The generated raw data is highly dimensional and complex, suffers from baseline problems, misalignments, long peak tails and strong non-linearities that must be corrected to extract chemically relevant features from samples. In this work, we present our GCIMS R package, which includes spectra loading, metadata handling, denoising, baseline correction, spectral and chromatographic alignment, peak detection, integration, and peak clustering to produce a peak table ready for multivariate data analysis. We discuss package design decisions, and, for illustration purposes, we show a case study of sex discrimination on the basis of the volatile compounds in urine samples. The GCIMS package provides a user-friendly workflow for non-code developers to process their raw data samples.7 p.application/pdfengcc-by-nc-nd (c) Oller Moreno, Sergio et al., 2023http://creativecommons.org/licenses/by-nc-nd/4.0/Cromatografia de gasosEspectroscòpia de mobilitat d'ionsCompostos orgànics volàtilsGas chromatographyIon mobility spectroscopyVolatile organic compoundsinfo:eu-repo/semantics/article7391332024-04-12info:eu-repo/semantics/openAccess6604508