Dataset Information

RBiomirGS: an all-in-one miRNA gene set analysis solution featuring target mRNA mapping and expression profile integration.

ABSTRACT: Background: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. 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. Methods:The 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. Results:By 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. Conclusions:With 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).

SUBMITTER: Zhang J

PROVIDER: S-EPMC5768164 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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RBiomirGS: an all-in-one miRNA gene set analysis solution featuring target mRNA mapping and expression profile integration.

Zhang Jing J Storey Kenneth B KB

PeerJ 20180112

<h4>Background</h4>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 ...[more]

PMID: 29340253

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Project description:miRNAs are small non-coding RNAs that regulate gene expression by binding to the 3'-UTR of genes. Many recent studies have reported that miRNAs play important biological roles by regulating specific mRNAs or genes. Many sequence-based target prediction algorithms have been developed to predict miRNA targets. However, these methods are not designed for condition-specific target predictions and produce many false positives; thus, expression-based target prediction algorithms have been developed for condition-specific target predictions. A typical strategy to utilize expression data is to leverage the negative control roles of miRNAs on genes. To control false positives, a stringent cutoff value is typically set, but in this case, these methods tend to reject many true target relationships, i.e., false negatives. To overcome these limitations, additional information should be utilized. The literature is probably the best resource that we can utilize. Recent literature mining systems compile millions of articles with experiments designed for specific biological questions, and the systems provide a function to search for specific information. To utilize the literature information, we used a literature mining system, BEST, that automatically extracts information from the literature in PubMed and that allows the user to perform searches of the literature with any English words. By integrating omics data analysis methods and BEST, we developed Context-MMIA, a miRNA-mRNA target prediction method that combines expression data analysis results and the literature information extracted based on the user-specified context. In the pathway enrichment analysis using genes included in the top 200 miRNA-targets, Context-MMIA outperformed the four existing target prediction methods that we tested. In another test on whether prediction methods can re-produce experimentally validated target relationships, Context-MMIA outperformed the four existing target prediction methods. In summary, Context-MMIA allows the user to specify a context of the experimental data to predict miRNA targets, and we believe that Context-MMIA is very useful for predicting condition-specific miRNA targets.

Dataset Information

RBiomirGS: an all-in-one miRNA gene set analysis solution featuring target mRNA mapping and expression profile integration.

Publications

RBiomirGS: an all-in-one miRNA gene set analysis solution featuring target mRNA mapping and expression profile integration.

Similar Datasets

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