circtools

circtools performs computational analyses of circular RNAs (circRNAs) from high-throughput sequencing data to detect circRNA candidates, reconstruct internal sequences, assess RNase R resistance, screen for RNA-binding protein (RBP) binding site enrichment, perform statistical testing, and design circRNA-specific primers.

Key Features:

• CircRNA Detection: Identifies circRNA candidates from high-throughput sequencing data by leveraging back-splicing signals.
• Internal Sequence Reconstruction: Reconstructs internal circRNA sequences to enable structural characterization.
• Quality Checking: Performs quality assessment of identified circRNA candidates to evaluate integrity and accuracy.
• Statistical Testing: Provides statistical analyses to assess significance of circRNA detection and comparisons.
• RBP Binding Site Screening: Screens circRNAs for enrichment of RNA-binding protein (RBP) binding sites.
• Differential Exon RNase R Resistance Analysis: Analyzes exon-level RNase R resistance to distinguish circRNAs from linear RNAs.
• CircRNA-Specific Primer Design: Designs primers that target circRNA back-splice junctions for experimental validation.
• Visualization: Generates visualizations to support interpretation of circRNA detection and characterization results.
• Result Export: Exports analysis results into commonly used formats for downstream use.

Scientific Applications:

• CircRNA discovery and annotation: Detection and cataloging of circRNA candidates from sequencing experiments.
• Structural characterization: Reconstruction of internal circRNA sequences to investigate exon composition and structure.
• RBP interaction analysis: Identification of RBP binding site enrichment on circRNAs to suggest potential interactions.
• RNase R resistance profiling: Use of exon-level RNase R resistance analysis to differentiate circular from linear transcripts.
• Statistical and differential analysis: Statistical validation and comparison of circRNA expression or detection across conditions.
• Experimental validation support: Design of circRNA-specific primers for PCR-based validation of predicted circRNAs.

Methodology:

circtools is a modular, Python-based framework that processes high-throughput sequencing data to detect circRNAs via back-splicing signals and implements modules for internal sequence reconstruction, quality assessment, statistical testing, RBP binding site enrichment screening, differential exon RNase R resistance analysis, and circRNA-specific primer design.