Abstract
BackgroundMultiplecompeting bioinformatics tools exist for next-generation sequencing data analysis. Many of these tools are available as R/Bioconductor modules, and it can be challenging for the bench biologist without any programming background to quickly analyse genomics data. Here, we present an application that is designed to be simple to use, while leveraging the power of R as the analysis engine behind the scenes.ResultsGenome Informatics Data Explorer (Guide) is a desktop application designed for the bench biologist to analyse RNA-seq and microarray gene expression data. It requires a text file of summarised read counts or expression values as input data, and performs differential expression analyses at both the gene and pathway level. It uses well-established R/Bioconductor packages such as limma for its analyses, without requiring the user to have specific knowledge of the underlying R functions. Results are presented in figures or interactive tables which integrate useful data from multiple sources such as gene annotation and orthologue data. Advanced options include the ability to edit R commands to customise the analysis pipeline.ConclusionsGuide is a desktop application designed to query gene expression data in a user-friendly way while automatically communicating with R. Its customisation options make it possible to use different bioinformatics tools available through R/Bioconductor for its analyses, while keeping the core usage simple. Guide is written in the cross-platform framework of Qt, and is freely available for use from http://guide.wehi.edu.au.
Highlights
Multiple competing bioinformatics tools exist for next-generation sequencing data analysis
Since the vast majority of bioinformatics methods developed within the RNAseq and microarray data analysis end up as R packages [5], Guide makes some commonly used packages such as limma [6] readily accessible to the user without having to understand the details of the package, or having to use R directly
Guide can perform background correction and quantile normalisation [18] automatically for Illumina Mouse WG-6 v2.0 array, making it more convenient for the user by requiring only the raw data as input. These types of support for microarrays may be increased in future versions based on user demand
Summary
Genome Informatics Data Explorer (Guide) is a desktop application designed for the bench biologist to analyse RNA-seq and microarray gene expression data. It requires a text file of summarised read counts or expression values as input data, and performs differential expression analyses at both the gene and pathway level. It uses well-established R/Bioconductor packages such as limma for its analyses, without requiring the user to have specific knowledge of the underlying R functions. Advanced options include the ability to edit R commands to customise the analysis pipeline
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