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cvlr: finding heterogeneously methylated genomic regions using ONT reads

SUMMARY: Nanopore reads encode information on the methylation status of cytosines in CpG dinucleotides. The length of the reads makes it comparatively easy to look at patterns consisting of multiple loci; here, we exploit this property to search for regions where one can define subpopulations of mol...

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Detalles Bibliográficos
Autores principales: Raineri, Emanuele, Alberola i Pla, Mariona, Dabad, Marc, Heath, Simon
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9887406/
https://www.ncbi.nlm.nih.gov/pubmed/36726731
http://dx.doi.org/10.1093/bioadv/vbac101
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author Raineri, Emanuele
Alberola i Pla, Mariona
Dabad, Marc
Heath, Simon
author_facet Raineri, Emanuele
Alberola i Pla, Mariona
Dabad, Marc
Heath, Simon
author_sort Raineri, Emanuele
collection PubMed
description SUMMARY: Nanopore reads encode information on the methylation status of cytosines in CpG dinucleotides. The length of the reads makes it comparatively easy to look at patterns consisting of multiple loci; here, we exploit this property to search for regions where one can define subpopulations of molecules based on methylation patterns. As an example, we run our clustering algorithm on known imprinted genes; we also scan chromosome 15 looking for windows corresponding to heterogeneous methylation. Our software can also compute the covariance of methylation across these regions while keeping into account the mixture of different types of reads. AVAILABILITY AND IMPLEMENTATION: https://github.com/EmanueleRaineri/cvlr. CONTACT: simon.heath@cnag.crg.eu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics Advances online.
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spelling pubmed-98874062023-01-31 cvlr: finding heterogeneously methylated genomic regions using ONT reads Raineri, Emanuele Alberola i Pla, Mariona Dabad, Marc Heath, Simon Bioinform Adv Applications Note SUMMARY: Nanopore reads encode information on the methylation status of cytosines in CpG dinucleotides. The length of the reads makes it comparatively easy to look at patterns consisting of multiple loci; here, we exploit this property to search for regions where one can define subpopulations of molecules based on methylation patterns. As an example, we run our clustering algorithm on known imprinted genes; we also scan chromosome 15 looking for windows corresponding to heterogeneous methylation. Our software can also compute the covariance of methylation across these regions while keeping into account the mixture of different types of reads. AVAILABILITY AND IMPLEMENTATION: https://github.com/EmanueleRaineri/cvlr. CONTACT: simon.heath@cnag.crg.eu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics Advances online. Oxford University Press 2023-01-23 /pmc/articles/PMC9887406/ /pubmed/36726731 http://dx.doi.org/10.1093/bioadv/vbac101 Text en © The Author(s) 2023. Published by Oxford University Press. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Applications Note
Raineri, Emanuele
Alberola i Pla, Mariona
Dabad, Marc
Heath, Simon
cvlr: finding heterogeneously methylated genomic regions using ONT reads
title cvlr: finding heterogeneously methylated genomic regions using ONT reads
title_full cvlr: finding heterogeneously methylated genomic regions using ONT reads
title_fullStr cvlr: finding heterogeneously methylated genomic regions using ONT reads
title_full_unstemmed cvlr: finding heterogeneously methylated genomic regions using ONT reads
title_short cvlr: finding heterogeneously methylated genomic regions using ONT reads
title_sort cvlr: finding heterogeneously methylated genomic regions using ont reads
topic Applications Note
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9887406/
https://www.ncbi.nlm.nih.gov/pubmed/36726731
http://dx.doi.org/10.1093/bioadv/vbac101
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