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DEIVA: a web application for interactive visual analysis of differential gene expression profiles.

Jayson Harshbarger¹, Anton Kratz¹, Piero Carninci²

¹RIKEN Center for Life Science Technologies, RIKEN Yokohama Institute, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa, 230-0045, Japan.

|January 8, 2017

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Differential gene expression (DGE) analysis identifies RNA abundance changes between biological states. DEIVA is a user-friendly web application for easily sharing and analyzing DGE results, improving gene discovery.

Area of Science:

Bioinformatics
Computational Biology
Genomics

Background:

Differential gene expression (DGE) analysis is crucial for identifying gene or RNA abundance variations across different biological conditions.
Current DGE analysis results often require complex statistical software or custom algorithms for interpretation.
A need exists for accessible tools to share and analyze DGE statistical test results, facilitating gene identification.

Purpose of the Study:

To develop a user-friendly, web-based application for analyzing differential gene expression data.
To provide an intuitive platform for locating and identifying genes within DGE statistical test results.
To enable seamless sharing and collaborative analysis of DGE findings.

Main Methods:

Development of DEIVA, a free and open-source, browser-based single-page application (SPA).

Keywords:

Differential gene expression Interactive visual analysis RNA-seq Visualization Web application

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Implementation of interactive and intuitive features for gene identification and analysis.

Design for scalability to accommodate large user numbers and extensive datasets.

Main Results:

DEIVA enables immediate, interactive, and intuitive locating and identification of single or multiple genes.
The application is designed for high scalability, supporting numerous users and large datasets.
DEIVA offers a user-friendly interface for inspecting and analyzing DGE statistical test results.

Conclusions:

DEIVA provides a unique combination of features for simplified DGE analysis.
The application emphasizes ease of use, lowering the barrier for researchers to interpret DGE data.
DEIVA facilitates efficient gene discovery and analysis from DGE studies.