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@odisce

Odiscé

Data Science team

Welcome to the public repository for the Odisce team, providing a comprehensive suite of packages for (metabol)omics data processing and analysis.

Detailed tutorials about this workflow can be found e.g. in the vignettes of the phenomis, ropls, and biosigner packages.

Feel free to contact us for any question.

PackageDescriptionReference
Preprocessing
ionshedSegmenting LC-MS raw dataDechaumet et al.
MassGATUntargeted detection and annotation of LC-HRMS dataPinart et al. (2026). bioRxiv
proFIAPreprocessing of FIA-HRMS dataDelabrière et al. (2017). Bioinformatics
ptairMSPre-processing PTR-TOF-MS DataRoquencourt et al. (2022). Bioinformatics
Spec2XtractPre-processing of MS/MS raw spectraDechaumet et al.
DIANMFPre-processing of SWATH DIA dataKaraki et al. (2024). EUSIPCO
Post-processing
phenomisPost-processing and univariate analysis of MS dataImbert et al. (2021). Sci. Data.
Machine learning
roplsPCA, PLS(-DA) and OPLS(-DA) for multivariate analysis and feature selection of omics dataThévenot et al. (2015). J. Proteome Res.
biosignerSignature discovery from omics dataRinaudo et al. (2016). Front. Mol. Biosci.
ProMetISMulti-omics phenotyping of the LAT and MX2 knockout miceImbert et al. (2021). Sci. Data.
Cheminformatics
Spec2AnnotAnnotation of MS/MS spectraDechaumet et al.
mineMS2Annotation of spectral libraries with exact fragmentation patternsDelabrière, Gianfrotta et al. (2025). J. Cheminform.
biodbA library and a development framework for connecting to chemical and biological databasesRoger et al.

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  1. mineMS2 mineMS2Public

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    Annotation of spectral libraries with exact fragmentation patterns

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  2. Spec2Xtract Spec2XtractPublic

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  3. phenomis phenomisPublic

    Postprocessing and univariate analysis of omics data

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  4. Spec2Annot Spec2AnnotPublic

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