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An alternative, alignment-based approach for telomere length estimation using whole-genome NGS data. We have performed its extensive validation using both synthetic and experimental data. Comparison of Computel with TelSeq showed that our approach outperforms the latter and allows for more flexibility and convenience of telomere length estimation in different genomes. The general workflow of mean telomere length estimation by Computel consists of the following steps: (1) building a telomeric index, (2) mapping reads to the telomeric index, (3) coverage calculation at the telomeric index, (4) determination of mean coverage at reference genome (optional), (5) estimation of mean telomere length.

Telomerecat / Telomere Computational Analysis Tool

Estimates telomere length from cancer whole genome sequencing (WGS) data. Telomerecat calculates and corrects the number of Interstitial telomeric repeat (ITR)-originating reads without consideration for how these highly repetitive reads are aligned to a reference genome. It is designed to be applicable to cancer experiments as it does not assume a given number of telomeres. It also correlates with existing computational and experimental methods as well as with sample donor age.


A tool for estimating telomere content from human whole-genome sequencing data. TelomereHunter is designed to take BAM files from a tumor and a matching control sample as input. However, it is also possible to run TelomereHunter with one input file. TelomereHunter extracts and sorts telomeric reads from the input sample(s). For the estimation of telomere content, GC biases are taken into account. Finally, the results of TelomereHunter are visualized in several diagrams. In contrast to existing tools, TelomereHunter takes alignment information into account and reports the abundance of variant repeats in telomeric sequences.