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Int. J. Mol. Sci. 2017, 18(2), 274; doi:10.3390/ijms18020274

SpidermiR: An R/Bioconductor Package for Integrative Analysis with miRNA Data

1
Institute of Molecular Bioimaging and Physiology National Research Council (IBFM-CNR), Segrate (Mi) 20090, Italy
2
Interuniversity Institute of Bioinformatics in Brussels (IB)2, Brussels 1050, Belgium
3
Machine Learning Group (MLG), Department d’Informatique, Universite libre de Bruxelles (ULB), Brussels 1050, Belgium
4
Department of Genetics Ribeirao Preto Medical School, University of Sao Paulo, Ribeirao Preto, Sao Paulo 14049-900, Brazil
5
Department of Neurosurgery, Henry Ford Hospital, Detroit, MI 48202, USA
6
Department of Informatics, Systems and Communication, University of Milan-Bicocca, Milan 20125, Italy
7
SYSBIO Centre of Systems Biology (SYSBIO), Milan 20126, Italy
*
Authors to whom correspondence should be addressed.
Academic Editor: Li Lin
Received: 1 December 2016 / Revised: 23 January 2017 / Accepted: 24 January 2017 / Published: 27 January 2017
(This article belongs to the Special Issue Transcriptome Profiling in Human Diseases)
View Full-Text   |   Download PDF [1139 KB, uploaded 4 February 2017]   |  

Abstract

Gene Regulatory Networks (GRNs) control many biological systems, but how such network coordination is shaped is still unknown. GRNs can be subdivided into basic connections that describe how the network members interact e.g., co-expression, physical interaction, co-localization, genetic influence, pathways, and shared protein domains. The important regulatory mechanisms of these networks involve miRNAs. We developed an R/Bioconductor package, namely SpidermiR, which offers an easy access to both GRNs and miRNAs to the end user, and integrates this information with differentially expressed genes obtained from The Cancer Genome Atlas. Specifically, SpidermiR allows the users to: (i) query and download GRNs and miRNAs from validated and predicted repositories; (ii) integrate miRNAs with GRNs in order to obtain miRNA–gene–gene and miRNA–protein–protein interactions, and to analyze miRNA GRNs in order to identify miRNA–gene communities; and (iii) graphically visualize the results of the analyses. These analyses can be performed through a single interface and without the need for any downloads. The full data sets are then rapidly integrated and processed locally. View Full-Text
Keywords: microRNA; network; protein; gene microRNA; network; protein; gene
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Cava, C.; Colaprico, A.; Bertoli, G.; Graudenzi, A.; Silva, T.C.; Olsen, C.; Noushmehr, H.; Bontempi, G.; Mauri, G.; Castiglioni, I. SpidermiR: An R/Bioconductor Package for Integrative Analysis with miRNA Data. Int. J. Mol. Sci. 2017, 18, 274.

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