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Bioinformatics. 2019 Mar 1;35(5):880-882. doi: 10.1093/bioinformatics/bty721.

ImaGEO: integrative gene expression meta-analysis from GEO database.

Author information

1
Bioinformatics Unit, GENYO Centre for Genomics and Oncological Research: Pfizer/University of Granada/Andalusian Regional Government, PTS Granada, Granada, Spain.
2
Area of Medical Genomics, GENYO Centre for Genomics and Oncological Research: Pfizer/University of Granada/Andalusian Regional Government, PTS Granada, Granada, Spain.
3
Atrys Health, Barcelona, Spain.
4
Unit of Chronic Inflammatory Diseases, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden.

Abstract

SUMMARY:

The Gene Expression Omnibus (GEO) database provides an invaluable resource of publicly available gene expression data that can be integrated and analyzed to derive new hypothesis and knowledge. In this context, gene expression meta-analysis (geMAs) is increasingly used in several fields to improve study reproducibility and discovering robust biomarkers. Nevertheless, integrating data is not straightforward without bioinformatics expertise. Here, we present ImaGEO, a web tool for geMAs that implements a complete and comprehensive meta-analysis workflow starting from GEO dataset identifiers. The application integrates GEO datasets, applies different meta-analysis techniques and provides functional analysis results in an easy-to-use environment. ImaGEO is a powerful and useful resource that allows researchers to integrate and perform meta-analysis of GEO datasets to lead robust findings for biomarker discovery studies.

AVAILABILITY AND IMPLEMENTATION:

ImaGEO is accessible at http://bioinfo.genyo.es/imageo/.

SUPPLEMENTARY INFORMATION:

Supplementary data are available at Bioinformatics online.

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