TelomereHunter

TelomereHunter estimates telomere content and characterizes telomere composition and variant repeats from high-throughput sequencing data to analyze telomere maintenance mechanisms in cancer genomes.

Key Features:

• In silico estimation: Estimates telomere content and composition directly from high-throughput sequencing data including whole genome sequencing (WGS), whole exome sequencing (WES), and whole genome bisulfite sequencing (WGBS).
• Singleton telomere variant extraction: Extracts singleton telomere variant repeats to aid identification and subclassification of alternative lengthening of telomeres (ALT) phenotypes.
• Diagnostic diagrams and machine-readable outputs: Produces diagnostic diagrams and machine-readable output files for downstream analyses.
• Correlation with experimental measurements: Shows strong correlation with telomere qPCR (r = 0.94), reports correlation for WGBS and matched controls (r = 0.78), and improved correlation after normalization with controls (r = 0.91).
• Versatility across sequencing types: Applicable to WGS, WES, and WGBS data and benefits from matched control samples for normalization and improved accuracy.

Scientific Applications:

• Telomere maintenance mechanism analysis: Enables characterization of telomere maintenance mechanisms and detection/subclassification of ALT phenotypes in cancer genomes.
• Cohort-scale cancer genomics studies: Supports analysis of large cancer genome cohorts for research and diagnostic investigations of telomere dynamics and their molecular footprints.

Methodology:

Processes WGS/WES/WGBS sequencing data to estimate telomere content and composition, extracts singleton telomere variant repeats, generates diagnostic diagrams and machine-readable outputs, and performs correlation analyses with telomere qPCR and matched-control normalization.