MAGE: An Open-Source Tool for Meta-Analysis of Gene Expression Studies

被引:1
|
作者
Tamposis, Ioannis A. [1 ]
Manios, Georgios A. [1 ]
Charitou, Theodosia [1 ]
Vennou, Konstantina E. [1 ]
Kontou, Panagiota, I [2 ]
Bagos, Pantelis G. [1 ]
机构
[1] Univ Thessaly, Dept Comp Sci & Biomed Informat, Lamia 35131, Greece
[2] Univ Thessaly, Dept Math, Lamia 35131, Greece
来源
BIOLOGY-BASEL | 2022年 / 11卷 / 06期
关键词
meta-analysis; gene expression studies; multiple outcomes; differentially expressed genes; enrichment analysis; PATHWAYS;
D O I
10.3390/biology11060895
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
Simple Summary In this work we present MAGE, an open-source Python package developed for the meta-analysis of gene expression data. It contains functions to convert probes to gene identifiers, and to perform standard meta-analysis, meta-analysis with bootstrap standard errors, and meta-analysis of multiple outcomes, as well as functional enrichment analysis. Additionally, visualizations for every function of this software package are provided. MAGE is available both in a standalone version and as a webserver. MAGE (Meta-Analysis of Gene Expression) is a Python open-source software package designed to perform meta-analysis and functional enrichment analysis of gene expression data. We incorporate standard methods for the meta-analysis of gene expression studies, bootstrap standard errors, corrections for multiple testing, and meta-analysis of multiple outcomes. Importantly, the MAGE toolkit includes additional features for the conversion of probes to gene identifiers, and for conducting functional enrichment analysis, with annotated results, of statistically significant enriched terms in several formats. Along with the tool itself, a web-based infrastructure was also developed to support the features of this package.
引用
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页数:13
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