circMeta

circMeta provides a computational framework for comprehensive analysis of circular RNAs, including annotation of genomic features that regulate circRNA biogenesis and rigorous differential expression analysis.

Key Features:

• Genomic Feature Annotation Module (circFeature): Provides comprehensive annotation of genomic features associated with circRNA biogenesis, including length of introns flanking circularized exons, presence of repetitive elements such as Alu and SINEs, competition scores for forming circRNAs, and RNA editing in back-splicing flanking introns.
• Two-Stage Differential Expression Approach (circJuncDE): Utilizes circular junction reads to quantitatively compare circRNA levels across conditions.
• Bayesian Hierarchical Model (circCLRDE): Models the ratio of circular reads to linear reads at back-splicing sites to analyze spatial and temporal regulation of circRNA production.

Scientific Applications:

• False Discovery Rate Control: Provides improved control over false discovery rates while maintaining comparable statistical power relative to existing methods.
• Functional Network Discovery: Enables identification of differentially expressed circRNAs implicated in Gene Ontology terms and circRNA–miRNA–mRNA networks that are not detectable by traditional mRNA differential expression methods.
• Experimental Validation: Supports selection of top DE circRNAs validated by RT-qPCR using divergent primers spanning back-splicing junctions.

Methodology:

circMeta integrates three primary computational modules—circFeature for genomic feature annotation, circJuncDE implementing a two-stage DE approach based on circular junction reads, and circCLRDE implementing a Bayesian hierarchical model on circular-to-linear read ratios at back-splicing sites.