Protocol to infer and analyze miRNA sponge modules in heterogeneous data using miRSM 2.0

MicroRNA (miRNA) sponges synergistically modulate physiological and pathological processes in the form of modules or clusters. Here, we present a protocol for inferring and analyzing miRNA sponge modules in heterogeneous data using the R package miRSM 2.0. We describe steps for identifying gene modules, inferring miRNA sponge modules at multi-sample and single-sample levels, and performing modular analysis. From the perspective of computational biology, miRSM 2.0 has the potential to advance our understanding of the role of miRNA sponges in diseases. For complete details on the use and execution of this protocol, please refer to Zhang et al.<sup>1</sup><sup>,</sup><sup>2</sup><sup>,</sup><sup>3</sup>.

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Publication Details

Journal
STAR Protocols
Published
2024-09-17
DOI
https://doi.org/10.1016/j.xpro.2024.103317
Citations
1
Primary Topic
Cancer-related molecular mechanisms research
Type
article
Field-Weighted Citation Impact
0.29

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article

Protocol to infer and analyze miRNA sponge modules in heterogeneous data using miRSM 2.0

Xuemei Wei, Chunwen Zhao, Junpeng Zhang, Haolin Yang
1 citations
STAR Protocols
Cancer-related molecular mechanisms research
0.29
article

Protocol to infer and analyze miRNA sponge modules in heterogeneous data using miRSM 2.0

Xuemei Wei, Chunwen Zhao, Junpeng Zhang, Haolin Yang
article en
1 citations

Abstract

MicroRNA (miRNA) sponges synergistically modulate physiological and pathological processes in the form of modules or clusters. Here, we present a protocol for inferring and analyzing miRNA sponge modules in heterogeneous data using the R package miRSM 2.0. We describe steps for identifying gene modules, inferring miRNA sponge modules at multi-sample and single-sample levels, and performing modular analysis. From the perspective of computational biology, miRSM 2.0 has the potential to advance our understanding of the role of miRNA sponges in diseases. For complete details on the use and execution of this protocol, please refer to Zhang et al.<sup>1</sup><sup>,</sup><sup>2</sup><sup>,</sup><sup>3</sup>.

STAR ProtocolsVol. 5(4)
Dali University (CN)
National Natural Science Foundation of China, Dali University
Openalex Percentile: Top 39%
Cancer-related molecular mechanisms research
0.29
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