Healthc Inform Res.  2016 Apr;22(2):81-88. 10.4258/hir.2016.22.2.81.

GEE: An Informatics Tool for Gene Expression Data Explore

• Lee SY
• Park CH
• Yoon JH
• Yun S
• Kim JH

• KMID: 2166935
• DOI: http://doi.org/10.4258/hir.2016.22.2.81

Abstract

OBJECTIVES
Major public high-throughput functional genomic data repositories, including the Gene Expression Omnibus (GEO) and ArrayExpress have rapidly expanded. As a result, a large number of diverse high-throughput functional genomic data retrieval systems have been developed. However, high-throughput functional genomic data retrieval remains challenging.
METHODS
We developed Gene Expression data Explore (GEE), the first powerful, flexible web and mobile search application for searching whole-genome epigenetic data and microarray data in public databases, such as GEO and ArrayExpress.
RESULTS
GEE provides an elaborate, convenient interface of query generation competences not available via various high-throughput functional genomic data retrieval systems, including GEO, ArrayExpress, and Atlas. In particular, GEE provides a suitable query generator using eVOC, the Experimental Factor Ontology (EFO), which is well represented with a variety of high-throughput functional genomic data experimental conditions. In addition, GEE provides an experimental design query constructor (EDQC), which provides elaborate retrieval filter conditions when the user designs real experiments.
CONCLUSIONS
The web version of GEE is available at http://www.snubi.org/software/gee, and its app version is available from the Apple App Store.

Keyword

Microarray Analysis; Search Engine; RNA Sequence; Mobile Applications

MeSH Terms

Base Sequence
Epigenomics
Gene Expression*
Informatics*
Information Storage and Retrieval
Microarray Analysis
Mobile Applications
Research Design
Search Engine

Figure

• 

  Figure 1 Example search (search parameters are representative in example page). (A) is the web version of Gene Expression data Explore (GEE) and (B) is the app version of GEE.

• 

  Figure 2 System (A) and search schema (B) of Gene Expression data Explore (GEE).

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  Figure 3 Search performance comparison of previous highthroughput functional genomic data searching systems and Gene Expression data Explorer (GEE). GEO: Gene Expression Omnibus, AR: ArrayExpress.

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