Jasmine Dumas1, Michael A Gargano2, Garrett M Dancik2. 1. College of Computing and Digital Media, DePaul University, Chicago, IL, USA. 2. Department of Mathematics and Computer Science, Eastern Connecticut State University, Willimantic, CT, USA.
Abstract
The Gene Expression Omnibus (GEO) is a public repository of gene expression data. Although GEO has its own tool, GEO2R, for data analysis, evaluation of single genes is not straightforward and survival analysis in specific GEO datasets is not possible without bioinformatics expertise. We describe a web application, shinyGEO, that allows a user to download gene expression data sets directly from GEO in order to perform differential expression and survival analysis for a gene of interest. In addition, shinyGEO supports customized graphics, sample selection, data export and R code generation so that all analyses are reproducible. The availability of shinyGEO makes GEO datasets more accessible to non-bioinformaticians, promising to lead to better understanding of biological processes and genetic diseases such as cancer. AVAILABILITY AND IMPLEMENTATION: Web application and source code are available from http://gdancik.github.io/shinyGEO/ CONTACT: dancikg@easternct.eduSupplementary information: Supplementary data are available at Bioinformatics online.
The Gene Expression Omnibus (GEO) is a public repository of gene expression data. Although GEO has its own tool, GEO2R, for data analysis, evaluation of single genes is not straightforward and survival analysis in specific GEO datasets is not possible without bioinformatics expertise. We describe a web application, shinyGEO, that allows a user to download gene expression data sets directly from GEO in order to perform differential expression and survival analysis for a gene of interest. In addition, shinyGEO supports customized graphics, sample selection, data export and R code generation so that all analyses are reproducible. The availability of shinyGEO makes GEO datasets more accessible to non-bioinformaticians, promising to lead to better understanding of biological processes and genetic diseases such as cancer. AVAILABILITY AND IMPLEMENTATION: Web application and source code are available from http://gdancik.github.io/shinyGEO/ CONTACT: dancikg@easternct.eduSupplementary information: Supplementary data are available at Bioinformatics online.
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