Amanida: an R package for meta-analysis of metabolomics non-integral data
- 1. 1 Department of Electrical Electronic Engineering and Automation, Universitat Rovira i Virgili, IISPV, 43007, Tarragona, Spain; 2 Metabolomics Interdisciplinary Group, Department of Nutrition and Metabo-lism, Institut d'Investigació Sanitària Pere Virgili, 43201 Reus, Catalonia, Spain; 3 Biomedical Research Centre in Diabetes and Associated Metabolic Disorders (CIBERDEM), ISCIII, 28029, Madrid, Spain;
- 2. 4 Department of Biostatistics, Universitat Rovira i Virgili, 43201 Reus, Catalonia, Spain;
- 3. 5 Oncology Department, Hospital Universitari Sant Joan de Reus. Institut d'Investigació Sanitària Pere Virgili, Universitat Rovira i Virgili, 43204, Reus, Spain;
- 4. 1 Department of Electrical Electronic Engineering and Automation, Universitat Rovira i Virgili, IISPV, 43007, Tarragona, Spain; 2 Metabolomics Interdisciplinary Group, Department of Nutrition and Metabo-lism, Institut d'Investigació Sanitària Pere Virgili, 43201 Reus, Catalonia, Spain; 3 Biomedical Research Centre in Diabetes and Associated Metabolic Disorders (CIBERDEM), ISCIII, 28029, Madrid, Spain; 6 NIH West Coast Metabolomics Center, University of California Davis, 95616, Davis, United States.
Description
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 behaviors (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: Amanida code and documentation are at CRAN and https://github.com/mariallr/amanida.
Supplementary information: Supplementary information is available at Bioinformatics online.
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