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Guide: a desktop application for analysing gene expression data.

¹The Walter and Eliza Hall Institute of Medical Research, 1G Royal Parade, Parkville, 3052, Melbourne, Australia. jchoi@wehi.edu.au.

|October 8, 2013

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Genome Informatics Data Explorer (Guide) simplifies gene expression analysis for bench biologists. This user-friendly application leverages R/Bioconductor for RNA-seq and microarray data, making complex bioinformatics accessible.

Area of Science:

Bioinformatics
Genomics
Computational Biology

Background:

Numerous bioinformatics tools exist for next-generation sequencing data analysis.
Many tools are R/Bioconductor modules, posing challenges for biologists without programming skills.
A need exists for user-friendly tools to analyze genomics data.

Purpose of the Study:

To present a desktop application, Genome Informatics Data Explorer (Guide), for bench biologists.
To provide a simple yet powerful tool for analyzing RNA-seq and microarray gene expression data.
To enable gene expression analysis without requiring programming expertise.

Main Methods:

Guide is a desktop application utilizing R/Bioconductor packages like limma for analysis.
Input data includes summarized read counts or expression values.

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Differential expression analysis is performed at both gene and pathway levels.

Main Results:

Guide analyzes RNA-seq and microarray gene expression data.
Results are presented in interactive figures and tables with integrated annotation and orthologue data.
Advanced users can customize the analysis pipeline by editing R commands.

Conclusions:

Guide offers a user-friendly interface for gene expression data analysis, interfacing with R.
Customization options allow integration of various R/Bioconductor tools while maintaining simplicity.
The application is cross-platform (Qt) and freely available.