Abstract
BackgroundWith the continuous discovery of microRNA’s (miRNA) association with a wide range of biological and cellular processes, expression profile-based functional characterization of such post-transcriptional regulation is crucial for revealing its significance behind particular phenotypes. Profound advancement in bioinformatics has been made to enable in depth investigation of miRNA’s role in regulating cellular and molecular events, resulting in a huge quantity of software packages covering different aspects of miRNA functional analysis. Therefore, an all-in-one software solution is in demand for a comprehensive yet highly efficient workflow. Here we present RBiomirGS, an R package for a miRNA gene set (GS) analysis.MethodsThe package utilizes multiple databases for target mRNA mapping, estimates miRNA effect on the target mRNAs through miRNA expression profile and conducts a logistic regression-based GS enrichment. Additionally, human ortholog Entrez ID conversion functionality is included for target mRNAs.ResultsBy incorporating all the core steps into one package, RBiomirGS eliminates the need for switching between different software packages. The modular structure of RBiomirGS enables various access points to the analysis, with which users can choose the most relevant functionalities for their workflow.ConclusionsWith RBiomirGS, users are able to assess the functional significance of the miRNA expression profile under the corresponding experimental condition by minimal input and intervention. Accordingly, RBiomirGS encompasses an all-in-one solution for miRNA GS analysis. RBiomirGS is available on GitHub (http://github.com/jzhangc/RBiomirGS). More information including instruction and examples can be found on website (http://kenstoreylab.com/?page_id=2865).
Highlights
MicroRNA is a ∼22 nucleotide long small RNA species and is mostly recognized as a negative gene expression regulator on a post-transcriptional level (He & Hannon, 2004). miRNAs have been proposed as biomarkers and/or therapeutic targetsHow to cite this article Zhang and Storey (2018), RBiomirGS: an all-in-one miRNA gene set analysis solution featuring target mRNA mapping and expression profile integration
We demonstrate the usage and performance of RBiomirGS using the liver data from a study assessing the role of miRNAs in facilitating daily torpor in hibernating South American marsupials (Hadj-Moussa et al, 2016)
We found that the iteratively reweighted least square (IWLS) method with parallel computing enabled with the Unix operating system exclusive FORK mode took the least amount of time to converge for KEGG analysis (Fig. 5, based on three repeats)
Summary
How to cite this article Zhang and Storey (2018), RBiomirGS: an all-in-one miRNA gene set analysis solution featuring target mRNA mapping and expression profile integration. Several GS techniques have been developed to directly incorporate differential expression (DE) results, such as gene set enrichment analysis (GSEA) (Subramanian et al, 2005). With the continuous discovery of microRNA’s (miRNA) association with a wide range of biological and cellular processes, expression profile-based functional characterization of such post-transcriptional regulation is crucial for revealing its significance behind particular phenotypes. Profound advancement in bioinformatics has been made to enable in depth investigation of miRNA’s role in regulating cellular and molecular events, resulting in a huge quantity of software packages covering different aspects of miRNA functional analysis. More information including instruction and examples can be found on website (http://kenstoreylab.com/?page_id=2865)
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