Current Technologies for Measuring or Predicting Telomere Length from Genomic Datasets
The gold standard for measuring telomere length is technically challenging, which limits its use in large population studies. Numerous bioinformatics tools have recently been developed to estimate telomere length using high-throughput sequencing data. This allows for scaling up telomere length estim...
Guardado en:
| Autores principales: | , |
|---|---|
| Formato: | Capítulo de libro |
| Lenguaje: | inglés |
| Publicado: |
IntechOpen
2024
|
| Materias: | |
| Acceso en línea: | https://www.intechopen.com/chapters/88254 |
| Etiquetas: |
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
| Sumario: | The gold standard for measuring telomere length is technically challenging, which limits its use in large population studies. Numerous bioinformatics tools have recently been developed to estimate telomere length using high-throughput sequencing data. This allows for scaling up telomere length estimates in large datasets. Telomere length depends substantially on genetics, and many genetic studies have looked at this relationship, which provides an opportunity to predict telomere length from genotyping data. However, in part because environment also significantly affects telomere length, the accuracy of telomere length predictions and estimates made from genomic data remains uncertain. In this chapter, we will summarize currently available bioinformatics tools for predicting or measuring telomere length from genomics datasets, and we will discuss each method’s limitations and advantages. |
|---|---|
| ISBN: | 978-0-85014-057-6 |
| DOI: | 10.5772/intechopen.113048 |