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scGHOST: Identifying single-cell 3D genome subcompartments
New single-cell Hi-C (scHi-C) technologies enable probing of the genome-wide cell-to-cell variability in 3D genome organization from individual cells. Several computational methods have been developed to reveal single-cell 3D genome features based on scHi-C data, including A/B compartments, topologi...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Cold Spring Harbor Laboratory
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10245874/ https://www.ncbi.nlm.nih.gov/pubmed/37292994 http://dx.doi.org/10.1101/2023.05.24.542032 |
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author | Xiong, Kyle Zhang, Ruochi Ma, Jian |
author_facet | Xiong, Kyle Zhang, Ruochi Ma, Jian |
author_sort | Xiong, Kyle |
collection | PubMed |
description | New single-cell Hi-C (scHi-C) technologies enable probing of the genome-wide cell-to-cell variability in 3D genome organization from individual cells. Several computational methods have been developed to reveal single-cell 3D genome features based on scHi-C data, including A/B compartments, topologically-associating domains, and chromatin loops. However, no scHi-C analysis method currently exists for annotating single-cell subcompartments, which are crucial for providing a more refined view of large-scale chromosome spatial localization in single cells. Here, we present scGhost, a single-cell subcompartment annotation method based on graph embedding with constrained random walk sampling. Applications of scGhost to scHi-C data and single-cell 3D genome imaging data demonstrate the reliable identification of single-cell subcompartments and offer new insights into cell-to-cell variability of nuclear subcompartments. Using scHi-C data from the human prefrontal cortex, scGhost identifies cell type-specific subcompartments that are strongly connected to cell type-specific gene expression, suggesting the functional implications of single-cell subcompartments. Overall, scGhost is an effective new method for single-cell 3D genome subcompartment annotation based on scHi-C data for a broad range of biological contexts. |
format | Online Article Text |
id | pubmed-10245874 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Cold Spring Harbor Laboratory |
record_format | MEDLINE/PubMed |
spelling | pubmed-102458742023-06-08 scGHOST: Identifying single-cell 3D genome subcompartments Xiong, Kyle Zhang, Ruochi Ma, Jian bioRxiv Article New single-cell Hi-C (scHi-C) technologies enable probing of the genome-wide cell-to-cell variability in 3D genome organization from individual cells. Several computational methods have been developed to reveal single-cell 3D genome features based on scHi-C data, including A/B compartments, topologically-associating domains, and chromatin loops. However, no scHi-C analysis method currently exists for annotating single-cell subcompartments, which are crucial for providing a more refined view of large-scale chromosome spatial localization in single cells. Here, we present scGhost, a single-cell subcompartment annotation method based on graph embedding with constrained random walk sampling. Applications of scGhost to scHi-C data and single-cell 3D genome imaging data demonstrate the reliable identification of single-cell subcompartments and offer new insights into cell-to-cell variability of nuclear subcompartments. Using scHi-C data from the human prefrontal cortex, scGhost identifies cell type-specific subcompartments that are strongly connected to cell type-specific gene expression, suggesting the functional implications of single-cell subcompartments. Overall, scGhost is an effective new method for single-cell 3D genome subcompartment annotation based on scHi-C data for a broad range of biological contexts. Cold Spring Harbor Laboratory 2023-05-25 /pmc/articles/PMC10245874/ /pubmed/37292994 http://dx.doi.org/10.1101/2023.05.24.542032 Text en https://creativecommons.org/licenses/by-nc-nd/4.0/This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (https://creativecommons.org/licenses/by-nc-nd/4.0/) , which allows reusers to copy and distribute the material in any medium or format in unadapted form only, for noncommercial purposes only, and only so long as attribution is given to the creator. |
spellingShingle | Article Xiong, Kyle Zhang, Ruochi Ma, Jian scGHOST: Identifying single-cell 3D genome subcompartments |
title | scGHOST: Identifying single-cell 3D genome subcompartments |
title_full | scGHOST: Identifying single-cell 3D genome subcompartments |
title_fullStr | scGHOST: Identifying single-cell 3D genome subcompartments |
title_full_unstemmed | scGHOST: Identifying single-cell 3D genome subcompartments |
title_short | scGHOST: Identifying single-cell 3D genome subcompartments |
title_sort | scghost: identifying single-cell 3d genome subcompartments |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10245874/ https://www.ncbi.nlm.nih.gov/pubmed/37292994 http://dx.doi.org/10.1101/2023.05.24.542032 |
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