Authors

James H.R. Farmery, University of Cambridge
Mike L. Smith, European Molecular Biology Laboratory
Aarnoud Huissoon, Birmingham Heartlands
Abigail Furnell, University of Cambridge
Adam Mead, John Radcliffe Hospital
Adam P. Levine, University College London
Adnan Manzur, Great Ormond Street Hospital for Children NHS Foundation Trust
Adrian Thrasher, Great Ormond Street Hospital for Children NHS Foundation Trust
Alan Greenhalgh, Newcastle upon Tyne Hospitals NHS Foundation Trust
Alasdair Parker, Cambridge University Hospitals NHS Foundation Trust
Alba Sanchis-Juan, University of Cambridge
Alex Richter, University Hospitals Birmingham NHS Foundation Trust
Alice Gardham, Great Ormond Street Hospital for Children NHS Foundation Trust
Allan Lawrie, Royal Hallamshire Hospital
Aman Sohal, Birmingham Women's and Children's NHS Foundation Trust
Amanda Creaser-Myers, Royal Hallamshire Hospital
Amy Frary, University of Cambridge
Andreas Greinacher, University of Greifswald
Andreas Themistocleous, University of Oxford
Andrew J. Peacock, Golden Jubilee National Hospital
Andrew Marshall, Northern Care Alliance NHS Group
Andrew Mumford, University Hospitals Bristol and Weston NHS Foundation Trust
Andrew Rice, Imperial College London
Andrew Webster, Moorfields Eye Hospital NHS Foundation Trust
Angie Brady, Northwick Park Hospital
Ania Koziell, King's College London
Ania Manson, Cambridge University Hospitals NHS Foundation Trust
Anita Chandra, Cambridge University Hospitals NHS Foundation Trust
Anke Hensiek, Cambridge University Hospitals NHS Foundation Trust
Anna Huis In T. Veld, VU University Medical Center

Abstract

Telomere length is a risk factor in disease and the dynamics of telomere length are crucial to our understanding of cell replication and vitality. The proliferation of whole genome sequencing represents an unprecedented opportunity to glean new insights into telomere biology on a previously unimaginable scale. To this end, a number of approaches for estimating telomere length from whole-genome sequencing data have been proposed. Here we present Telomerecat, a novel approach to the estimation of telomere length. Previous methods have been dependent on the number of telomeres present in a cell being known, which may be problematic when analysing aneuploid cancer data and non-human samples. Telomerecat is designed to be agnostic to the number of telomeres present, making it suited for the purpose of estimating telomere length in cancer studies. Telomerecat also accounts for interstitial telomeric reads and presents a novel approach to dealing with sequencing errors. We show that Telomerecat performs well at telomere length estimation when compared to leading experimental and computational methods. Furthermore, we show that it detects expected patterns in longitudinal data, repeated measurements, and cross-species comparisons. We also apply the method to a cancer cell data, uncovering an interesting relationship with the underlying telomerase genotype.

DOI

10.1038/s41598-017-14403-y

Publication Date

2018-12-01

Publication Title

Scientific Reports

Volume

8

Issue

1

ISSN

2045-2322

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