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Sections SOFTWARE |
Software
Amanida for Meta-analysis (Bioinformatics, 2022): Amanida R package is a meta-analysis approach using only the most reported statistical parameters in the field of metabolomics: p-value and fold-change. The p-values are combined via Fisher's method and fold-changes are combined by averaging, both weighted by the study size (n). The amanida package includes several visualization options: a volcano plot for quantitative results, a vote plot for total regulation behaviors (up/down regulations) for each compound, and an explore plot of the vote-counting results with the number of times a compound is found upregulated or downregulated. Our solution is available as an R package at CRAN, and we have also created a dedicated website (https://ubidi.shinyapps.io/easy-amanida/).
Ref: Llambrich, M. et al. "Amanida: an R package for meta-analysis of metabolomics non-integral data", Bioinformatics, 2022 Jan 15; 38(2): 583-585, DOI: 10.1093/bioinformatics/btab591".
HERMES for LC-MS/MS (Nature Methods, 2021)(patent ES2767375B2): a conceptually novel experimental and computational method to acquire and process LC/MS-based metabolomics data. HERMES is a molecular formula-oriented and peak detection-free method that improves sensitivity, selectivity, and structural annotation of metabolites. The source code of RHermes is offered to the public as a freely accessible software package under the GNU GPL, version 3 license, and is available at https://github.com/RogerGinBer/RHermes and at Zenodo with accession number 5504163.
Ref: Giné, R. et al. "HERMES: a molecular-formula-oriented method to target the metabolome". Nature Methods. 2021 Nov;18(11):1370-1376.12. DOI: https://doi.org/10.1038/s41592-021-01307-z.
eRah for GC-MS (Analytical Chemistry, 2016): an integrated computational workflow that incorporates a novel spectral deconvolution method, alignment of spectra across samples, quantification, and automated identification of metabolites by spectral library matching.
Ref: Domingo-Almenara, X. et al. "eRah: A Computational Tool Integrating Spectral Deconvolution and Alignment with Quantification and Identification of Metabolites in GC/MS-Based Metabolomics". Analytical Chemistry, 2016 Oct 4;88(19):9821-9829.13. DOI: 10.1021/acs.analchem.6b02927
rMSIproc for MSImaging/single cell metabolomics (Bioinformatics, 2020): a computational tool that implements a full data processing workflow for MS Imaging experiments performed using TOF, Orbitrap or FT-based mass spectrometers. The tool provides a novel strategy for spectral alignment and recalibration, which allows processing multiple datasets simultaneously. This enables to perform a confident statistical analysis with multiple datasets from one or several experiments. rMSIproc is freely available at https://github.com/prafols/rMSIproc.
Ref: Ràfols, P. et al. "rMSIproc: an R package for mass spectrometry imaging data processing". Bioinformatics, 2020 Jun 1;36(11): 3618-3619. DOI: 10.1093/bioinformatics/btaa142