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shinyGEO - a web-based application for analyzing gene expression omnibus datasets

shinyGEO (http://gdancik.github.io/shinyGEO/) is a web-based tool that allows a user to download the expression and sample data from a Gene Expression Omnibus dataset, select a gene of interest, and perform a survival or differential expression analysis using the available data. For both analyses, shinyGEO produces publication-ready graphics and generates R code ensuring that all analyses are reproducible. The tool is developed using shiny, a web application framework for R, a language for statistical computing and graphics.

Latest updates: shinyGEO now allows for caching of GEO datasets and storage of data updates using docker volumes. Caching will result in much faster run times for commonly analyzed series and platforms.

Publications

If you use shinyGEO in your work, please cite the following Bioinformatics manuscript (link):

Dumas J, Gargano MA, Dancik GM. shinyGEO: a web-based application for analyzing Gene Expression Omnibus datasets. Bioinformatics. 2016 Dec 1;32(23):3679-3681.

The preferred way of running shinyGEO locally is through docker

  1. Download docker from https://www.docker.com/get-started

  2. Pull the docker image by running the following from your terminal (PowerShell on Windows) (Note: you should do this periodically to ensure that you are using the the most up-to-date version of shinyGEO).

    docker pull gdancik/shinygeo

  3. Run shinyGEO by copying and pasting the command to your terminal:

    docker run -it -p 3838:3838 --volume shinygeo-cache:/root/shinyGEO/cache --volume shinygeo-data:/root/shinyGEO/datasets gdancik/shinygeo

  4. View shinyGEO by opening a web browser and entering localhost:3838 into the address bar.

  5. If the dataset you wish to analyze does not appear in the dropdown, then you may click the Update button to update the available datasets. It is only necessary to update the data if the dataset of interest is not listed. Any updates will automatically be saved to a docker volume, as described below. Note that shinyGEO is designed to analyze only datasets whose experiment type is 'Expression profiling by array'; currently the analysis of other datasets is not supported.

Caching and docker volumes

When running shinyGEO as described above, docker volumes are used to store data so that data will persist from one shinyGEO session to the next. In particular, data downloaded from GEO is cached in the volume shinygeo-cache. Caching the data greatly increases the speed in which previously viewed datasets or platforms are loaded. From within shinyGEO, you can click on the "Cache" icon in the sidebar to view and manage the cache.

In addition, the available platform and series datasets are now stored in the volume shinygeo-datasets. Therefore, the available datasets will automatically be "saved" when clicking the update button.

If for any reason you wish to delete a volume, you can use the docker volume rm command, e.g.,

docker volume rm shinygeo-datasets

Alternatives for running shinyGEO

While using docker is preferred, you can also run shinyGEO from the web at https://gdancik.shinyapps.io/shinyGEO/.

About

shinyGEO is a project of the Bioinformatics Laboratory at Eastern Connecticut State University.

  • Main contributors: Jasmine Dumas, Michael Gargano*, Garrett M. Dancik, PhD
  • Additional contributors: Nataliia Romanenko*, Ken-Heng Liao*, Gregory Harper*, Brandon Spratt*

An asterisk (*) denotes an undergraduate Computer Science major from Eastern.

Funding

This work was supported, in part, by Google Summer of Code funding to JD in 2015.

Page theme

This page uses a slightly modified version of the Cayman theme (https://github.com/pages-themes/cayman)