This package provides the data sets and analyzes from the preclinical, proteomics, and metabolomics study of the LAT and MX2 knockout mice.
The package can be installed from GitHub with devtools::install_github("IFB-ElixirFr/ProMetIS").
Note regarding the recent versions of the phenomis package (>= 0.4.0): please set the argument output.c = "set" when using the phenomis::reading method to obtain a MultiDataSet instance as described in this vignette (otherwise, the output.c = "exp" default setting will generate a MutiAssayExperiment instance).
Etienne A. Thévenot (etienne.thevenot@cea.fr)
A total of 42 mice from the Lat-/- and Mx2-/- genotypes (as well as the wild-type controls), and from both sex, were analyzed by a series of phenomic (preclinical) measurements. Liver and plasma samples from all mice were further analyzed at the molecular level by proteomics and metabolomics.
The number of features after the post-processing step is shown for each of the 9 datasets (1 preclinical, 2 proteomics, 6 metabolomics). The number of annotated metabolites is indicated in squared brackets. The names of the metabolomics datasets include the reference to the chromatographic column (c18hypersil: Hypersil GOLD C18, hilic: ZIC-pHILIC, and c18acquity: Acquity HSS-T3) and the ionization mode (pos: positive, and neg: negative).
The data are available in the extdata folder, which is organized into subfolders corresponding to the successive steps of the analysis (e.g, 1_processed, 2_post_processed, 5_aggregated, etc.). Within each subfolder, the 9 datasets are stored as a triplet of tabular files containing the matrix of intensities (dataMatrix.tsv), the sample metadata (sampleMetadata.tsv) and the variable metadata (variableMetadata.tsv). For each step, a vignette describes the methods used to process the data. As an example, the 2_post_processed vignette details how the datasets were post-processed, between the 1_processed and the 2_post_processed folders. The tutorial vignette describes how to access the final aggregated data to perform integrative bioinformatic and biostatistic analyses.
The ProMetIS project is funded by five French National Infrastructures:
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PHENOMIN: Mouse Phenogenomics [ANR-10-INBS-0007]
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France Genomique [ANR-10-INBS-0009]
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ProFI: Proteomics [ANR-10-INBS-0008]
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MetaboHUB: Metabolomics and Fluxomics [ANR-11-INBS-0010]
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IFB: Bioinformatics [ANR-11-INBS-0013]
In particular, Alyssa Imbert is supported by a post-doctoral fellowship from IFB as part of the pilot projects in integrative bioinformatics.
CeCILL 2.1 free software license
ProMetIS: deep phenotyping of mouse models by combined proteomics and metabolomics analysis. Alyssa Imbert, Magali Rompais, Mohammed Selloum, Florence Castelli, Emmanuelle Mouton-Barbosa, Marion Brandolini-Bunlon, Emeline Chu-Van, Charlotte Joly, Aurélie Hirschler, Pierrick Roger, Thomas Burger, Sophie Leblanc, Tania Sorg, Sadia Ouzia, Yves Vandenbrouck, Claudine Médigue, Christophe Junot, Myriam Ferro, Estelle Pujos-Guillot, Anne Gonzalez de Peredo, François Fenaille, Christine Carapito, Yann Herault, and Etienne A. Thévenot. Scientific Data, 8. doi:10.1038/s41597-021-01095-3