Work

GSEA-InContext Explorer: An interactive visualization tool for putting gene set enrichment analysis results into biological context

Year: 2019

Type: preprint

Abstract: Summary GSEA-InContext Explorer is a Shiny app that allows users to perform two methods of gene set enrichment analysis (GSEA). The first, GSEAPreranked, applies the GSEA algorithm in which statistical significance is estimated from a null distribution of enrichment scores generated for randomly permuted gene sets. The second, GSEA-InContext, incorporates a user-defined set of background experiments to define the null distribution and calculate statistical significance. GSEA-InContext Explorer allows the user to build custom background sets from a compendium of over 5,700 curated experiments, run both GSEAPreranked and GSEA-InContext on their own uploaded experiment, and explore the results using an interactive interface. This tool will allow researchers to visualize gene sets that are commonly enriched across experiments and identify gene sets that are uniquely significant in their experiment, thus complementing current methods for interpreting gene set enrichment results. Availability and implementation The code for GSEA-InContext Explorer is available at: https://github.com/CostelloLab/GSEA-InContext_Explorer and the interactive tool is at: http://gsea-incontext_explorer.ngrok.io

Source: bioRxiv (Cold Spring Harbor Laboratory)

DOI: 10.1101/659847

Authors: Rani K. Powers, Anthony Sun, James C. Costello

Institutions: University of Colorado Anschutz, Colorado School of Mines, University of Colorado Cancer Center

Language: English

Topic: Bioinformatics and Genomic Networks

Subfield: Molecular Biology

Field: Biochemistry, Genetics and Molecular Biology

Domain: Life Sciences

Open Access status: green

Funders: Boettcher Foundation, National Institutes of Health

Awards: G9000069151, G9001225491