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.
CITATION STYLE
Llambrich, M., Correig, E., Gumà, J., Brezmes, J., & Cumeras, R. (2022). Amanida: an R package for meta-analysis of metabolomics non-integral data. Bioinformatics, 38(2), 583–585. https://doi.org/10.1093/bioinformatics/btab591
Mendeley helps you to discover research relevant for your work.