Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Data-driven prioritization of mouse strains for improved preclinical modeling of rare and common disease.

bioRxiv : the preprint server for biology·2026
Same author

Systematic benchmarking demonstrates large language models have not reached the diagnostic accuracy of traditional rare-disease decision support tools.

European journal of human genetics : EJHG·2026
Same author

A Phenotypic Paradigm for Cerebral Palsy Genetics.

medRxiv : the preprint server for health sciences·2026
Same author

An ITPR1 Variant in the IP3-ITPR1 Binding Pocket Associated With a Clinical Phenotype of Athetoid Cerebral Palsy.

American journal of medical genetics. Part A·2025
Same author

Expression of Aldehyde Dehydrogenase 1A1 in Relapse-Associated Cells in Acute Myeloid Leukemia.

Cells·2025
Same author

Leveraging generative AI to assist biocuration of medical actions for rare disease.

Bioinformatics advances·2025

Related Experiment Video

Updated: Mar 16, 2026

Development of Compendium for Esophageal Squamous Cell Carcinoma
03:36

Development of Compendium for Esophageal Squamous Cell Carcinoma

Published on: April 12, 2024

902

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

Jasmine Dumas1, Michael A Gargano2, Garrett M Dancik2

  • 1College of Computing and Digital Media, DePaul University, Chicago, IL, USA.

Bioinformatics (Oxford, England)
|August 10, 2016
PubMed
Summary
This summary is machine-generated.

shinyGEO simplifies gene expression analysis for researchers. This web application allows users to perform differential expression and survival analysis on Gene Expression Omnibus (GEO) datasets, making complex data more accessible.

More Related Videos

A Protocol for Using Gene Set Enrichment Analysis to Identify the Appropriate Animal Model for Translational Research
09:35

A Protocol for Using Gene Set Enrichment Analysis to Identify the Appropriate Animal Model for Translational Research

Published on: August 16, 2017

18.4K
Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues
10:12

Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues

Published on: January 10, 2019

19.2K

Related Experiment Videos

Last Updated: Mar 16, 2026

Development of Compendium for Esophageal Squamous Cell Carcinoma
03:36

Development of Compendium for Esophageal Squamous Cell Carcinoma

Published on: April 12, 2024

902
A Protocol for Using Gene Set Enrichment Analysis to Identify the Appropriate Animal Model for Translational Research
09:35

A Protocol for Using Gene Set Enrichment Analysis to Identify the Appropriate Animal Model for Translational Research

Published on: August 16, 2017

18.4K
Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues
10:12

Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues

Published on: January 10, 2019

19.2K

Area of Science:

  • Bioinformatics
  • Genomics
  • Computational Biology

Background:

  • The Gene Expression Omnibus (GEO) is a vital public repository for gene expression data.
  • Existing tools like GEO2R have limitations in single-gene evaluation and survival analysis for specific datasets.
  • Bioinformatics expertise is often required to fully leverage GEO data.

Purpose of the Study:

  • To introduce shinyGEO, a web application designed to enhance accessibility of GEO datasets.
  • To enable users to perform differential expression and survival analysis on specific genes within GEO datasets.
  • To facilitate reproducible research by supporting customized graphics, sample selection, and R code generation.

Main Methods:

  • Development of a user-friendly web application, shinyGEO.
  • Integration with the Gene Expression Omnibus (GEO) repository for direct data download.
  • Implementation of differential expression and survival analysis functionalities.
  • Inclusion of features for customized graphics, sample selection, and R code generation.

Main Results:

  • shinyGEO provides a straightforward interface for analyzing gene expression data from GEO.
  • Users can perform both differential expression and survival analyses without extensive bioinformatics knowledge.
  • The application ensures reproducibility of analyses through generated R code and customizable outputs.
  • GEO datasets become more accessible to a wider range of researchers, including non-bioinformaticians.

Conclusions:

  • shinyGEO significantly lowers the barrier to entry for analyzing complex gene expression data from GEO.
  • The tool empowers researchers to explore biological processes and genetic diseases like cancer more effectively.
  • Increased accessibility of GEO data through shinyGEO is expected to accelerate biological discovery.