MIRIA

MIRIA integrates statistical and visualization methods to analyze RNA editing site data and characterize RNA editing patterns in mammals.

Key Features:

• Statistical Analysis: Provides RNA editing type statistics to categorize different RNA edit types across datasets.
• Editing Level Statistics: Computes quantitative editing level statistics to assess editing frequency and distribution.
• Genomic Feature Annotations: Annotates genomic features associated with RNA editing sites to provide biological context.
• Genome-wide Distribution and Visualization: Generates genome-wide analyses and visualizations to identify patterns and hotspots of RNA editing activity.
• Tissue-specific Analysis: Analyzes high-throughput RNA sequencing (RNA-seq) data across tissues to assess tissue-specific RNA editing.
• Conservation Analysis: Assesses conservation of RNA editing sites to infer evolutionary significance.
• Data Integration: Integrates high-throughput RNA-seq data from eight tissues across seven species for comparative analyses.

Scientific Applications:

• Statistical profiling: Enables basic statistical assessments of RNA editing types and editing levels across samples.
• Tissue- and species-specific studies: Supports comparative analysis of RNA editing across eight tissues and seven species using RNA-seq data.
• Evolutionary conservation studies: Facilitates conservation analysis to identify evolutionarily conserved RNA editing sites.
• Functional inference: Aids investigation of potential functional roles of RNA editing through genomic annotations and distribution analyses.

Methodology:

Integration and analysis of high-throughput RNA-seq data to compute RNA editing type statistics and editing level statistics, perform genomic feature annotation, generate genome-wide distribution visualizations, conduct tissue-specific analyses, and assess conservation of RNA editing sites.