Available Software for Meta-analyses of Genome-wide Expression Studies
1PhD Program in Health Sciences, School of Medicine, Universidad Antonio Nariño, Bogotá, Colombia.
Current Genomics
|June 2, 2020
Summary
Meta-analysis of Genome-Wide Expression Studies (GWES) aids in identifying differentially expressed genes. This review covers software tools for GWES meta-analysis, discussing their features and future directions.
Area of Science:
- Genomics and Bioinformatics
- Transcriptomics and Gene Expression Analysis
Background:
- Genome-Wide Expression Studies (GWES) have proliferated due to advances in transcriptomic methods.
- Microarray platforms were historically used for GWES to compare gene expression across sample groups.
- Meta-analysis of GWES is crucial for robust identification of differentially expressed genes.
Purpose of the Study:
- To review and describe available software packages for conducting meta-analysis of Genome-Wide Expression Studies (GWES).
- To evaluate the features, advantages, and disadvantages of various GWES meta-analysis tools.
- To propose key areas for future development in GWES meta-analysis software.
Main Methods:
- Systematic review of software for GWES meta-analysis.
- Description of seven Bioconductor packages and five CRAN packages.
- Inclusion of nine previously described programs and four online programs.
Main Results:
- A comprehensive overview of the current landscape of GWES meta-analysis software.
- Detailed descriptions of specific tools available on Bioconductor, CRAN, and as standalone programs/online resources.
- Comparative analysis of the strengths and weaknesses of the reviewed software.
Conclusions:
- The availability of diverse software tools facilitates GWES meta-analysis for identifying key genes.
- Understanding the features and limitations of these tools is essential for researchers.
- Future developments should focus on enhancing usability and analytical capabilities for GWES meta-analysis.
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