proFIA: A data preprocessing workflow for Flow Injection Analysis coupled to High-Resolution Mass Spectrometry

Alexis Delabrière 1, * Ulli Hohenester 2 Benoit Colsch 2 Christophe Junot 2 François Fenaille 2 Etienne Thévenot 1, *
* Auteur correspondant
1 LADIS - Laboratoire d'analyse des données et d'intelligence des systèmes
DM2I - Département Métrologie Instrumentation & Information : DRT/LIST/DM2I
2 LEMM - Laboratoire d'Etude du Métabolisme des Médicaments
SPI - Service de Pharmacologie et Immunoanalyse : DRF/JOLIOT
Abstract : Motivation: Flow Injection Analysis coupled to High-Resolution Mass Spectrometry (FIA-HRMS) is a promising approach for high-throughput metabolomics. FIA-HRMS data, however, cannot be preprocessed with current software tools which rely on liquid chromatography separation, or handle low resolution data only. Results: We thus developed the proFIA package, which implements a suite of innovative algorithms to preprocess FIA-HRMS raw files, and generates the table of peak intensities. The workflow consists of 3 steps: i) noise estimation, peak detection and quantification, ii) peak grouping across samples, and iii) missing value imputation. In addition, we have implemented a new indicator to quantify the potential alteration of the feature peak shape due to matrix effect. The preprocessing is fast (less than 15 s per file), and the value of the main parameters (ppm and dmz) can be easily inferred from the mass resolution of the instrument. Application to two metabolomics datasets (including spiked serum samples) showed high precision (96%) and recall (98%) compared with manual integration. These results demonstrate that proFIA achieves very efficient and robust detection and quantification of FIA-HRMS data, and opens new opportunities for high-throughput phenotyping. Availability: The proFIA software (as well as the plasFIA data set) is available as an R package on the Bioconductor repository (http://bioconductor.org/packages/proFIA), and as a Galaxy module on the Main Toolshed (https://toolshed.g2.bx.psu.edu/) and on the Workflow4Metabolomics online infrastructure (http://workflow4metabolomics.org). Contacts: alexis.delabriere@cea.fr and etienne.thevenot@cea.fr.
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Contributeur : Etienne Thevenot <>
Soumis le : dimanche 13 août 2017 - 23:20:58
Dernière modification le : jeudi 27 septembre 2018 - 13:29:56

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Alexis Delabrière, Ulli Hohenester, Benoit Colsch, Christophe Junot, François Fenaille, et al.. proFIA: A data preprocessing workflow for Flow Injection Analysis coupled to High-Resolution Mass Spectrometry. Bioinformatics, Oxford University Press (OUP), 2017, 33 (23), pp.3767-3775. 〈https://doi.org/10.1093/bioinformatics/btx458〉. 〈10.1093/bioinformatics/btx458〉. 〈hal-01574347〉

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