README.md

In ethevenot/metabolis: Metabolomics Data Analysis

metabolis: An R package for metabolomics data analysis

Description

This package provides methods to perform the statistical analysis of metabolomics datasets. These methods include the reading of datasets (as 3 table dataMatrix, sampleMetadata and variableMetadata .tsv files) into an ExpressionSet object (metRead), quality control (metView) and transformation (metTransform) of the dataMatrix, and univariate hypothesis testing (metTest). Multivariate analysis and feature selection can be further performed with the ropls and biosigner packages, respectively (see the sacurine vignette).

Author

Etienne A. Thevenot et al.

This package was developed through fruitful discussions within our Metabolomics Data Sciences and Integration team at CEA (Incl Natacha Lenuzza, Philippe Rinaudo, Pierrick Roger, Alyssa Imbert, Camille Roquencourt), with experimenters from the Drug Metabolism Research Laboratory (Incl Aurelie Roux, Samia Boudah, Florence Castelli, Christophe Junot, Francois Fenaille), and with biostatisticians from the MetaboHUB infrastructure for metabolomics and fluxomics (Incl Marie Tremblay-Franco, Jean-Francois Martin, Melanie Petera). The functions have been wrapped into Galaxy modules and integrated into the Workflow4metabolomics with the help of the W4M Core Team.

Methods

Formats

3 tabular file format used for import/export

Input (i.e. preprocessed) data consists of a 'samples times variables' matrix of intensities (datMatrix numeric matrix), in addition to sample and variable metadata (sampleMetadata and variableMetadata data frames). Theses 3 tables can be conveniently imported to/exported from R as tabular files:

ExpressionSet class used within the data analysis workflow

Within the R workflow, the ExpressionSet class perfectly handles these 3 tables (for additional information about ExpressionSet class, see the 'An introduction to Biobase and ExpressionSets' documentation from the Biobase package).

Installation

install.packages("devtools", dep=TRUE)  
devtools::install_github("https://github.com/ethevenot/metabolis")

Tutorial

See the metabolis vignette for a detailed example of the analysis of a metabolomics dataset.

Please cite

• Thévenot, E.A., Roux, A., Xu, Y., Ezan, E., and Junot, C. (2015). Analysis of the human adult urinary metabolome variations with age, body mass index and gender by implementing a comprehensive workflow for univariate and OPLS statistical analyses. Journal of Proteome Research 14, 3322–3335. doi:10.1021/acs.jproteome.5b00354

• Guitton, Y., Tremblay-Franco, M., Le Corguillé, G., G., Martin, J.-F., Pétéra, M., Roger-Mele, P., Delabrière, A., Goulitquer, S., Monsoor, M., Duperier, C., Canlet, C., Servien, R., Tardivel, P., Caron, C., Giacomoni, F., and Thévenot, E. (2017). Create, run, share, publish, and reference your LC-MS, FIA-MS, GC-MS, and NMR data analysis workflows with the Workflow4Metabolomics 3.0 Galaxy online infrastructure for metabolomics. The International Journal of Biochemistry & Cell Biology 93, 89–101. doi:10.1016/j.biocel.2017.07.002

ethevenot/metabolis documentation built on June 28, 2019, 1:27 p.m.