The Gene Expression Omnibus database

By Emily Clough, Tanya Barrett. Statistical Genomics, 2016

1,980 citations recorded by the source corpus.

The Gene Expression Omnibus (GEO) database is an international public repository that archives and freely distributes high-throughput gene expression and other functional genomics data sets. Created in 2000 as a worldwide resource for gene expression studies, GEO has evolved with rapidly changing technologies and now accepts high-throughput data for many other data applications, including those that examine genome methylation, chromatin structure, and genome–protein interactions. GEO supports community-derived reporting standards that specify provision of several critical study elements including raw data, processed data, and descriptive metadata. The database not only provides access to data for tens of thousands of studies, but also offers various Web-based tools and strategies that enable users to locate data relevant to their specific interests, as well as to visualize and analyze the data. This chapter includes detailed descriptions of methods to query and download GEO data and use the analysis and visualization tools. The GEO homepage is at http://www.ncbi.nlm.nih.gov/geo/.

Subfields: Molecular Biology

View Paper: https://www.semanticscholar.org/paper/73a254f05fa694dc11a5efc5a033a8f1a4c84fd0

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Citations in the corpus

• The Application of Deep Learning in Cancer Prognosis Prediction (2020, background): “The Gene Expression Omnibus (GEO) database is a public data repository storing microarray and next-generation sequencing (NGS) data, as well as other high-throughput functional genomic datasets, such as genome methylation, chromatin structure, genomic mutation/copy number variation, protein profilin”
• HERB: a high-throughput experiment- and reference-guided database of traditional Chinese medicine (2020, neutral): “the Gene Expression Omnibus (GEO) repository (4).”
• Metabolomics and Multi-Omics Integration: A Survey of Computational Methods and Resources (2020, methodology): “Single-omic repositories include MetaboLights [36] and Metabolomics Workbench [37] for metabolome data, the PRoteomics IDEntifications Database [38] for proteome data, Gene Expression Omnibus [39] and Sequence Read Archive [40] for genomic data, the Encyclopedia of DNA Elements [41] for functional e”