ceRNAshiny

ceRNAshiny constructs and analyzes competing endogenous RNA (ceRNA) networks to characterize interactions among non-coding RNAs, pseudogenes, circular RNAs, and messenger RNAs and to support differential gene analysis and functional annotation within an R/Shiny environment.

Key Features:

• Integration of computational methods: Incorporates established computational techniques to analyze ceRNA interactions.
• Differential gene analysis: Provides functionality for differential gene expression analysis of RNAs involved in ceRNA networks.
• Functional annotation: Enables functional annotation of genes and RNAs linked to ceRNA network components.
• ceRNA network visualization: Supplies visualization capabilities to construct and examine complex ceRNA network structures.
• RNA biotype support: Explicitly analyzes non-coding RNAs, pseudogenes, circular RNAs (circRNAs), and messenger RNAs (mRNAs) within ceRNA contexts.
• Neurodegenerative disease demo data: Includes demo data for neurodegenerative diseases, specifically Parkinson's disease.
• R/Shiny implementation: Implemented in R using the Shiny framework.

Scientific Applications:

• ceRNA interaction analysis: Characterizes competing endogenous RNA interactions among ncRNAs, pseudogenes, circRNAs, and mRNAs.
• Post-transcriptional regulation studies: Supports investigation of post-transcriptional regulatory mechanisms mediated by ceRNA networks.
• Differential expression-driven functional studies: Facilitates linking differential gene expression to functional annotation within ceRNA contexts.
• Neurodegenerative disease research: Enables analysis of ceRNA network alterations in neurodegenerative conditions, including Parkinson's disease.

Methodology:

Implemented in R/Shiny and leverages established computational techniques for differential gene analysis, functional annotation, and analysis of RNA interactions to construct and examine ceRNA networks.