ExpressionDB – An open source platform for distributing genome-scale datasets

RNA-sequencing (RNA-seq) and microarrays are methods for measuring gene expression across the entire transcriptome. Recent advances have made these techniques practical and affordable for essentially any laboratory with experience in molecular biology. A variety of computational methods have been developed to decrease the amount of bioinformatics expertise necessary to analyze these data. Nevertheless, many barriers persist which discourage new labs from using functional genomics approaches. Since high-quality gene expression studies have enduring value as resources to the entire research community, it is of particular importance that small labs have the capacity to share their analyzed datasets with the research community.

Here researchers at the Washington University School of Medicine introduce ExpressionDB, an open source platform for visualizing RNA-seq and microarray data accommodating virtually any number of different samples. ExpressionDB is based on Shiny, a customizable web application which allows data sharing locally and online with customizable code written in R. ExpressionDB allows intuitive searches based on gene symbols, descriptions, or gene ontology terms, and it includes tools for dynamically filtering results based on expression level, fold change, and false-discovery rates. Built-in visualization tools include heatmaps, volcano plots, and principal component analysis, ensuring streamlined and consistent visualization to all users.

The ExpressionDB user interface is designed to showcase
RNA-seq data with straightforward visuals

rna-seq

Dot plots represent expression levels of different transcripts in different samples, with error bars representing +/- S.E.M. Results can be filtered by gene symbol, gene name/description, or Gene Ontology (GO) terms. 

The developers estimate that a demo database can be created in under one hour with minimal programming experience, and that a new database with user-supplied expression data can be completed and online in less than one day.

Availability – To aid the user in creating their own ExpressionDB, we have made all source code publicly available on GitHub (https://github.com/5c077/ExpressionDB) which includes an online tutorial with screenshots (https://github.com/5c077/ExpressionDB/wiki/User’s-Guide).

Hughes LD, Lewis SA, Hughes ME (2017) ExpressionDB: An open source platform for distributing genome-scale datasets. PLoS ONE12(11): e0187457. [article]

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