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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...

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Detalles Bibliográficos
Autores principales: Zhu, Hao, Liu, Tong, Wang, Zheng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2023
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/.
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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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