Cargando…
Metheor: Ultrafast DNA methylation heterogeneity calculation from bisulfite read alignments
Phased DNA methylation states within bisulfite sequencing reads are valuable source of information that can be used to estimate epigenetic diversity across cells as well as epigenomic instability in individual cells. Various measures capturing the heterogeneity of DNA methylation states have been pr...
Autores principales: | , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10062925/ https://www.ncbi.nlm.nih.gov/pubmed/36940213 http://dx.doi.org/10.1371/journal.pcbi.1010946 |
_version_ | 1785017597873356800 |
---|---|
author | Lee, Dohoon Koo, Bonil Yang, Jeewon Kim, Sun |
author_facet | Lee, Dohoon Koo, Bonil Yang, Jeewon Kim, Sun |
author_sort | Lee, Dohoon |
collection | PubMed |
description | Phased DNA methylation states within bisulfite sequencing reads are valuable source of information that can be used to estimate epigenetic diversity across cells as well as epigenomic instability in individual cells. Various measures capturing the heterogeneity of DNA methylation states have been proposed for a decade. However, in routine analyses on DNA methylation, this heterogeneity is often ignored by computing average methylation levels at CpG sites, even though such information exists in bisulfite sequencing data in the form of phased methylation states, or methylation patterns. In this study, to facilitate the application of the DNA methylation heterogeneity measures in downstream epigenomic analyses, we present a Rust-based, extremely fast and lightweight bioinformatics toolkit called Metheor. As the analysis of DNA methylation heterogeneity requires the examination of pairs or groups of CpGs throughout the genome, existing softwares suffer from high computational burden, which almost make a large-scale DNA methylation heterogeneity studies intractable for researchers with limited resources. In this study, we benchmark the performance of Metheor against existing code implementations for DNA methylation heterogeneity measures in three different scenarios of simulated bisulfite sequencing datasets. Metheor was shown to dramatically reduce the execution time up to 300-fold and memory footprint up to 60-fold, while producing identical results with the original implementation, thereby facilitating a large-scale study of DNA methylation heterogeneity profiles. To demonstrate the utility of the low computational burden of Metheor, we show that the methylation heterogeneity profiles of 928 cancer cell lines can be computed with standard computing resources. With those profiles, we reveal the association between DNA methylation heterogeneity and various omics features. Source code for Metheor is at https://github.com/dohlee/metheor and is freely available under the GPL-3.0 license. |
format | Online Article Text |
id | pubmed-10062925 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-100629252023-03-31 Metheor: Ultrafast DNA methylation heterogeneity calculation from bisulfite read alignments Lee, Dohoon Koo, Bonil Yang, Jeewon Kim, Sun PLoS Comput Biol Research Article Phased DNA methylation states within bisulfite sequencing reads are valuable source of information that can be used to estimate epigenetic diversity across cells as well as epigenomic instability in individual cells. Various measures capturing the heterogeneity of DNA methylation states have been proposed for a decade. However, in routine analyses on DNA methylation, this heterogeneity is often ignored by computing average methylation levels at CpG sites, even though such information exists in bisulfite sequencing data in the form of phased methylation states, or methylation patterns. In this study, to facilitate the application of the DNA methylation heterogeneity measures in downstream epigenomic analyses, we present a Rust-based, extremely fast and lightweight bioinformatics toolkit called Metheor. As the analysis of DNA methylation heterogeneity requires the examination of pairs or groups of CpGs throughout the genome, existing softwares suffer from high computational burden, which almost make a large-scale DNA methylation heterogeneity studies intractable for researchers with limited resources. In this study, we benchmark the performance of Metheor against existing code implementations for DNA methylation heterogeneity measures in three different scenarios of simulated bisulfite sequencing datasets. Metheor was shown to dramatically reduce the execution time up to 300-fold and memory footprint up to 60-fold, while producing identical results with the original implementation, thereby facilitating a large-scale study of DNA methylation heterogeneity profiles. To demonstrate the utility of the low computational burden of Metheor, we show that the methylation heterogeneity profiles of 928 cancer cell lines can be computed with standard computing resources. With those profiles, we reveal the association between DNA methylation heterogeneity and various omics features. Source code for Metheor is at https://github.com/dohlee/metheor and is freely available under the GPL-3.0 license. Public Library of Science 2023-03-20 /pmc/articles/PMC10062925/ /pubmed/36940213 http://dx.doi.org/10.1371/journal.pcbi.1010946 Text en © 2023 Lee et al 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 use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Lee, Dohoon Koo, Bonil Yang, Jeewon Kim, Sun Metheor: Ultrafast DNA methylation heterogeneity calculation from bisulfite read alignments |
title | Metheor: Ultrafast DNA methylation heterogeneity calculation from bisulfite read alignments |
title_full | Metheor: Ultrafast DNA methylation heterogeneity calculation from bisulfite read alignments |
title_fullStr | Metheor: Ultrafast DNA methylation heterogeneity calculation from bisulfite read alignments |
title_full_unstemmed | Metheor: Ultrafast DNA methylation heterogeneity calculation from bisulfite read alignments |
title_short | Metheor: Ultrafast DNA methylation heterogeneity calculation from bisulfite read alignments |
title_sort | metheor: ultrafast dna methylation heterogeneity calculation from bisulfite read alignments |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10062925/ https://www.ncbi.nlm.nih.gov/pubmed/36940213 http://dx.doi.org/10.1371/journal.pcbi.1010946 |
work_keys_str_mv | AT leedohoon metheorultrafastdnamethylationheterogeneitycalculationfrombisulfitereadalignments AT koobonil metheorultrafastdnamethylationheterogeneitycalculationfrombisulfitereadalignments AT yangjeewon metheorultrafastdnamethylationheterogeneitycalculationfrombisulfitereadalignments AT kimsun metheorultrafastdnamethylationheterogeneitycalculationfrombisulfitereadalignments |