RADAR

RADAR performs differential analysis of MeRIP-seq (Methylated RNA Immunoprecipitation Sequencing) data to identify differentially methylated loci for epitranscriptome profiling while accounting for variability using a random effect model.

Key Features:

• Detection of Differentially Methylated Loci: Identifies loci with altered methylation patterns from MeRIP-seq data using a random effect model.
• Accommodation of Variability: Handles variability in pre-immunoprecipitation expression levels and post-immunoprecipitation counts through distinct modeling strategies.
• Complex Study Design Compatibility: Integrates covariates into the analysis to support complex experimental designs.
• Enhanced Accuracy and Reproducibility: Performance evaluated with simulation studies and analyses of real datasets showing improved accuracy and reproducibility compared to existing methods.

Scientific Applications:

• Functional Genomics: Identifies differentially methylated sites to elucidate the effects of RNA modifications on gene regulation and expression.
• Disease Research: Characterizes alterations in RNA methylation patterns to inform disease mechanisms and potential biomarkers or therapeutic targets.
• Developmental Biology: Assesses dynamic regulation of RNA modifications during developmental processes.

Methodology:

Applies a random effect model to account for biological and technical variability in MeRIP-seq, incorporates covariates, and applies strategies to manage variability in pre-immunoprecipitation expression levels and post-immunoprecipitation counts; performance assessed via simulation studies and analyses of real datasets.