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Amanida: an R package for meta-analysis of metabolomics non-integral data

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 statist...

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Detalles Bibliográficos
Autores principales: Llambrich, Maria, Correig, Eudald, Gumà, Josep, Brezmes, Jesús, Cumeras, Raquel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8722753/
https://www.ncbi.nlm.nih.gov/pubmed/34406360
http://dx.doi.org/10.1093/bioinformatics/btab591
Descripción
Sumario: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.