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

被引:44
作者
Cava, Claudia [1 ]
Colaprico, Antonio [2 ,3 ]
Bertoli, Gloria [1 ]
Graudenzi, Alex [1 ]
Silva, Tiago C. [4 ]
Olsen, Catharina [2 ,3 ]
Noushmehr, Houtan [4 ,5 ]
Bontempi, Gianluca [2 ,3 ]
Mauri, Giancarlo [6 ,7 ]
Castiglioni, Isabella [1 ]
机构
[1] Inst Mol Bioimaging & Physiol Natl Res Council IB, I-20090 Segrate, Mi, Italy
[2] Interuniv Inst Bioinformat Brussels IB 2, B-1050 Brussels, Belgium
[3] Univ Libre Bruxelles, Dept Informat, Machine Learning Grp MLG, B-1050 Brussels, Belgium
[4] Univ Sao Paulo, Dept Genet, Ribeirao Preto Med Sch, BR-14049900 Sao Paulo, Brazil
[5] Henry Ford Hosp, Dept Neurosurg, Detroit, MI 48202 USA
[6] Univ Milano Bicocca, Dept Informat Syst & Commun, I-20125 Milan, Italy
[7] SYSBIO Ctr Syst Biol SYSBIO, I-20126 Milan, Italy
基金
巴西圣保罗研究基金会;
关键词
microRNA; network; protein; gene; MICRORNA-TARGET INTERACTIONS; PROSTATE; GENES; EXPRESSION; PREDICTION; CALCIFICATION; BIOMARKERS; PROGNOSIS; DIAGNOSIS; GENOMICS;
D O I
10.3390/ijms18020274
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
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.
引用
收藏
页数:14
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