miRspongeR

miRspongeR implements methods in R/Bioconductor to identify and analyze microRNA (miRNA) sponge interactions and modules—RNA entities containing multiple tandem miRNA response elements that sequester miRNAs from their target messenger RNAs (mRNAs)—to study miRNA-mediated gene regulation.


Key Features:

  • Identification of miRNA sponge interactions: miRspongeR provides seven popular methodologies and an integrative approach for identifying miRNA sponge interactions.
  • Validation of interactions: The package supports validation of identified miRNA sponge interactions.
  • Module identification: It facilitates identification of miRNA sponge modules, i.e., groups of sponges that may share common regulatory roles.
  • Functional enrichment analysis: Researchers can perform functional enrichment analysis on identified miRNA sponge modules to assess biological significance.
  • Survival analysis: The tool includes survival analysis capabilities to investigate associations between miRNA sponges and clinical outcomes, including cancer.

Scientific Applications:

  • Mechanistic studies: Dissecting regulatory roles of miRNA sponges in miRNA-mediated gene regulation.
  • Translational research: Associating miRNA sponge modules with clinical outcomes for applications such as cancer research.

Methodology:

The package applies a combination of computational techniques that integrate multiple methods for identifying miRNA sponge interactions, using an integrative approach to apply established methodologies to new datasets.

Topics

Details

License:
GPL-3.0
Maturity:
Mature
Cost:
Free of charge
Tool Type:
library
Operating Systems:
Linux, Windows, Mac
Programming Languages:
R
Added:
5/17/2019
Last Updated:
11/25/2024

Operations

Publications

Zhang J, Liu L, Xu T, Xie Y, Zhao C, Li J, Le TD. miRspongeR: an R/Bioconductor package for the identification and analysis of miRNA sponge interaction networks and modules. BMC Bioinformatics. 2019;20(1). doi:10.1186/s12859-019-2861-y. PMID:31077152. PMCID:PMC6509829.

PMID: 31077152
PMCID: PMC6509829
Funding: - National Natural Science Foundation of China: 61702069 - Applied Basic Research Foundation of Yunnan Province: 2017FB099 - National Health and Medical Research Council: 1123042 - Australian Research Council Discovery Grant: DP140103617

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