epialleleR: an R/Bioconductor package for sensitive allele-specific methylation analysis in NGS data.
DNA methylation
epigenetic mosaicism
epigenetics
methylation sequencing
somatic mosaicism
Journal
GigaScience
ISSN: 2047-217X
Titre abrégé: Gigascience
Pays: United States
ID NLM: 101596872
Informations de publication
Date de publication:
28 12 2022
28 12 2022
Historique:
received:
01
06
2023
revised:
03
08
2023
accepted:
26
09
2023
medline:
6
11
2023
pubmed:
3
11
2023
entrez:
3
11
2023
Statut:
ppublish
Résumé
Low-level mosaic epimutations within the BRCA1 gene promoter occur in 5-8% of healthy individuals and are associated with a significantly elevated risk of breast and ovarian cancer. Similar events may also affect other tumor suppressor genes, potentially being a significant contributor to cancer burden. While this opens a new area for translational research, detection of low-level mosaic epigenetic events requires highly sensitive and robust methodology for methylation analysis. We here present epialleleR, a computational framework for sensitive detection, quantification, and visualization of mosaic epimutations in methylation sequencing data. Analyzing simulated and real data sets, we provide in-depth assessments of epialleleR performance and show that linkage to epihaplotype data is necessary to detect low-level methylation events. The epialleleR is freely available at https://github.com/BBCG/epialleleR and https://bioconductor.org/packages/epialleleR/ as an open-source R/Bioconductor package.
Identifiants
pubmed: 37919976
pii: 7334271
doi: 10.1093/gigascience/giad087
pmc: PMC10622323
pii:
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Informations de copyright
© The Author(s) 2023. Published by Oxford University Press GigaScience.
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