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scHiMe: predicting single-cell DNA methylation levels based on single-cell Hi-C data
Recently a biochemistry experiment named methyl-3C was developed to simultaneously capture the chromosomal conformations and DNA methylation levels on individual single cells. However, the number of data sets generated from this experiment is still small in the scientific community compared with the...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10359091/ https://www.ncbi.nlm.nih.gov/pubmed/37302805 http://dx.doi.org/10.1093/bib/bbad223 |
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author | Zhu, Hao Liu, Tong Wang, Zheng |
author_facet | Zhu, Hao Liu, Tong Wang, Zheng |
author_sort | Zhu, Hao |
collection | PubMed |
description | Recently a biochemistry experiment named methyl-3C was developed to simultaneously capture the chromosomal conformations and DNA methylation levels on individual single cells. However, the number of data sets generated from this experiment is still small in the scientific community compared with the greater amount of single-cell Hi-C data generated from separate single cells. Therefore, a computational tool to predict single-cell methylation levels based on single-cell Hi-C data on the same individual cells is needed. We developed a graph transformer named scHiMe to accurately predict the base-pair-specific (bp-specific) methylation levels based on both single-cell Hi-C data and DNA nucleotide sequences. We benchmarked scHiMe for predicting the bp-specific methylation levels on all of the promoters of the human genome, all of the promoter regions together with the corresponding first exon and intron regions, and random regions on the whole genome. Our evaluation showed a high consistency between the predicted and methyl-3C-detected methylation levels. Moreover, the predicted DNA methylation levels resulted in accurate classifications of cells into different cell types, which indicated that our algorithm successfully captured the cell-to-cell variability in the single-cell Hi-C data. scHiMe is freely available at http://dna.cs.miami.edu/scHiMe/. |
format | Online Article Text |
id | pubmed-10359091 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-103590912023-07-21 scHiMe: predicting single-cell DNA methylation levels based on single-cell Hi-C data Zhu, Hao Liu, Tong Wang, Zheng Brief Bioinform Problem Solving Protocol Recently a biochemistry experiment named methyl-3C was developed to simultaneously capture the chromosomal conformations and DNA methylation levels on individual single cells. However, the number of data sets generated from this experiment is still small in the scientific community compared with the greater amount of single-cell Hi-C data generated from separate single cells. Therefore, a computational tool to predict single-cell methylation levels based on single-cell Hi-C data on the same individual cells is needed. We developed a graph transformer named scHiMe to accurately predict the base-pair-specific (bp-specific) methylation levels based on both single-cell Hi-C data and DNA nucleotide sequences. We benchmarked scHiMe for predicting the bp-specific methylation levels on all of the promoters of the human genome, all of the promoter regions together with the corresponding first exon and intron regions, and random regions on the whole genome. Our evaluation showed a high consistency between the predicted and methyl-3C-detected methylation levels. Moreover, the predicted DNA methylation levels resulted in accurate classifications of cells into different cell types, which indicated that our algorithm successfully captured the cell-to-cell variability in the single-cell Hi-C data. scHiMe is freely available at http://dna.cs.miami.edu/scHiMe/. Oxford University Press 2023-06-10 /pmc/articles/PMC10359091/ /pubmed/37302805 http://dx.doi.org/10.1093/bib/bbad223 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 | Problem Solving Protocol Zhu, Hao Liu, Tong Wang, Zheng scHiMe: predicting single-cell DNA methylation levels based on single-cell Hi-C data |
title | scHiMe: predicting single-cell DNA methylation levels based on single-cell Hi-C data |
title_full | scHiMe: predicting single-cell DNA methylation levels based on single-cell Hi-C data |
title_fullStr | scHiMe: predicting single-cell DNA methylation levels based on single-cell Hi-C data |
title_full_unstemmed | scHiMe: predicting single-cell DNA methylation levels based on single-cell Hi-C data |
title_short | scHiMe: predicting single-cell DNA methylation levels based on single-cell Hi-C data |
title_sort | schime: predicting single-cell dna methylation levels based on single-cell hi-c data |
topic | Problem Solving Protocol |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10359091/ https://www.ncbi.nlm.nih.gov/pubmed/37302805 http://dx.doi.org/10.1093/bib/bbad223 |
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