Telogator

Telogator reports chromosome-specific telomere lengths from long-read sequencing data for high-resolution analysis of telomere length variation.

Key Features:

• Chromosome-specific measurement: Reports telomere lengths for individual chromosomes using long-read sequencing data.
• Tailored telomere detection: Implements methods specifically tailored to detect and report telomeric repeats despite their repetitive sequence context.
• Simulation-based sensitivity: Demonstrates high sensitivity on simulated datasets across varying read lengths and error rates.
• Germline sample validation: Shows strong correlation with traditional short-read methods for reporting average telomere lengths in 10 germline samples.
• Subtelomere rearrangement analysis: Investigates common subtelomere rearrangements.
• Read-length requirement estimation: Determines the minimum read length required to accurately anchor telomere/subtelomere boundaries in samples with specific haplotypes.
• Implementation: Implemented in Python3.

Scientific Applications:

• Chromosome-specific variation detection: Identify chromosome-specific telomere length variations linked to disease.
• Biomarker discovery: Support biomarker identification for cancers and short telomere syndromes by resolving per-chromosome telomere lengths.
• Subtelomere characterization: Characterize common subtelomere rearrangements.
• Sequencing requirements assessment: Assess minimum sequencing read length requirements to anchor telomere/subtelomere boundaries for specific haplotypes.
• Cross-technology comparison: Compare long-read and short-read telomere length estimates in germline samples.

Methodology:

Analyzes long-read sequencing data; evaluates performance on simulated datasets varying read length and error rate; compares results to short-read average telomere length methods in 10 germline samples; investigates subtelomere rearrangements; estimates minimum read length for telomere/subtelomere anchoring; implemented in Python3.