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Updated: Oct 23, 2025

Author Spotlight: Emerging Technologies and Advanced Tools for Decoding Metabolomics Data Analysis
Published on: November 10, 2023
Amanida: an R package for meta-analysis of metabolomics non-integral data
Maria Llambrich1,2,3, Eudald Correig4, Josep Gumà5
1Department of Electrical Electronic Engineering and Automation, Universitat Rovira i Virgili, IISPV, 43007 Tarragona, Spain.
Summary:
The combination, analysis and evaluation of different studies which try to answer or solve the same scientific question, also known as a meta-analysis, plays a crucial role in answering relevant clinical relevant questions. Unfortunately, metabolomics studies rarely disclose all the statistical information needed to perform a meta-analysis. Here, we present a meta-analysis approach using only the most reported statistical parameters in this field: P-value and fold-change. The P-values are combined via Fisher's method and fold-changes 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 behaviours (up/down regulations) for each compound, and a explore plot of the vote-counting results with the number of times a compound is found upregulated or downregulated. In this way, it is very easy to detect discrepancies between studies at a first glance.
Availability And Implementation:
Amanida code and documentation are at CRAN and https://github.com/mariallr/amanida.
Supplementary Information:
Supplementary data are available at Bioinformatics online.
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