TelomereHunter2: Improved In silico Telomere Analysis Software for Precision Oncology and Single-cell Studies

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ID: 319375
2026
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Abstract
Abstract Motivation Telomere biology plays a critical role in multiple biological processes including carcinogenesis, aging, and genome stability. With increasing availability of DNA-sequence datasets, telomere length and composition are more frequently directly inferred in silico. The TelomereHunter software is used in genome research and precision oncology to study telomere maintenance mechanisms from routine sequencing data. However, bioinformatics tools face constant challenges such as increasing the number and size of genomic datasets, novel file formats and deprecating software components. Results We developed TelomereHunter2 (TH2) to create a sustainable framework for telomere analysis. By containerizing our software and improving the runtime by up to 74%, we simplify the integration of TH2 into diverse precision oncology workflows and computational environments. We also extended TH2 to support non-human genomes and single-cell sequencing approaches, broadening its applications across species and methodologies. We demonstrate TH2 improvements on a pilot dataset. Availability and implementation TelomereHunter2 is an open-source Python package released under the GPL-3.0 license. It is distributed via PyPI and the source code, documentation, and wiki are available at: https://github.com/ferdinand-popp/TelomereHunter2.
Reference Key
openalex_W7166854940 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Ferdinand Popp, Nicola Biondi, Urška Pogorevčnik, Nicholas Abad, H Chen, Yoann Pageaud, Benedikt Brors, Lars Feuerbach
Journal Bioinformatics advances
Year 2026
DOI
10.1093/bioadv/vbag187
URL
https://doi.org/10.1093/bioadv/vbag187
Keywords Keywords not found

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