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

被引:11
|
作者
Llambrich, Maria [1 ,2 ,3 ]
Correig, Eudald [4 ]
Guma, Josep [5 ]
Brezmes, Jesus [1 ,2 ,3 ]
Cumeras, Raquel [1 ,2 ,3 ,6 ]
机构
[1] Univ Rovira & Virgili, Dept Elect Elect Engn & Automat, IISPV, Tarragona 43007, Spain
[2] Inst Invest Sanitaria Pere Virgili, Dept Nutr & Metab, Metabol Interdisciplinary Grp, Reus 43201, Catalonia, Spain
[3] ISCIII, Biomed Res Ctr Diabet & Associated Metab Disorder, Madrid 28029, Spain
[4] Univ Rovira & Virgili, Dept Biostat, Reus 43201, Catalonia, Spain
[5] Univ Rovira & Virgili, Inst Invest Sanitaria Pere Virgili, Oncol Dept, Hosp Univ St Joan Reus, Reus 43204, Spain
[6] Univ Calif Davis, West Coast Metabol Ctr, Davis, CA 95616 USA
基金
欧盟地平线“2020”;
关键词
CANCER;
D O I
10.1093/bioinformatics/btab591
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
A 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.
引用
收藏
页码:583 / 585
页数:3
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