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Dynamic epigenetic mode analysis using spatial temporal clustering
BACKGROUND: Differentiation of human embryonic stem cells requires precise control of gene expression that depends on specific spatial and temporal epigenetic regulation. Recently available temporal epigenomic data derived from cellular differentiation processes provides an unprecedented opportunity...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5259871/ https://www.ncbi.nlm.nih.gov/pubmed/28155634 http://dx.doi.org/10.1186/s12859-016-1331-z |
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author | Gan, YangLan Tao, Han Zou, Guobing Yan, Cairong Guan, Jihong |
author_facet | Gan, YangLan Tao, Han Zou, Guobing Yan, Cairong Guan, Jihong |
author_sort | Gan, YangLan |
collection | PubMed |
description | BACKGROUND: Differentiation of human embryonic stem cells requires precise control of gene expression that depends on specific spatial and temporal epigenetic regulation. Recently available temporal epigenomic data derived from cellular differentiation processes provides an unprecedented opportunity for characterizing fundamental properties of epigenomic dynamics and revealing regulatory roles of epigenetic modifications. RESULTS: This paper presents a spatial temporal clustering approach, named STCluster, which exploits the temporal variation information of epigenomes to characterize dynamic epigenetic mode during cellular differentiation. This approach identifies significant spatial temporal patterns of epigenetic modifications along human embryonic stem cell differentiation and cluster regulatory sequences by their spatial temporal epigenetic patterns. CONCLUSIONS: The results show that this approach is effective in capturing epigenetic modification patterns associated with specific cell types. In addition, STCluster allows straightforward identification of coherent epigenetic modes in multiple cell types, indicating the ability in the establishment of the most conserved epigenetic signatures during cellular differentiation process. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12859-016-1331-z) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-5259871 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-52598712017-01-26 Dynamic epigenetic mode analysis using spatial temporal clustering Gan, YangLan Tao, Han Zou, Guobing Yan, Cairong Guan, Jihong BMC Bioinformatics Research BACKGROUND: Differentiation of human embryonic stem cells requires precise control of gene expression that depends on specific spatial and temporal epigenetic regulation. Recently available temporal epigenomic data derived from cellular differentiation processes provides an unprecedented opportunity for characterizing fundamental properties of epigenomic dynamics and revealing regulatory roles of epigenetic modifications. RESULTS: This paper presents a spatial temporal clustering approach, named STCluster, which exploits the temporal variation information of epigenomes to characterize dynamic epigenetic mode during cellular differentiation. This approach identifies significant spatial temporal patterns of epigenetic modifications along human embryonic stem cell differentiation and cluster regulatory sequences by their spatial temporal epigenetic patterns. CONCLUSIONS: The results show that this approach is effective in capturing epigenetic modification patterns associated with specific cell types. In addition, STCluster allows straightforward identification of coherent epigenetic modes in multiple cell types, indicating the ability in the establishment of the most conserved epigenetic signatures during cellular differentiation process. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12859-016-1331-z) contains supplementary material, which is available to authorized users. BioMed Central 2016-12-23 /pmc/articles/PMC5259871/ /pubmed/28155634 http://dx.doi.org/10.1186/s12859-016-1331-z Text en © The Author(s) 2016 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver(http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Gan, YangLan Tao, Han Zou, Guobing Yan, Cairong Guan, Jihong Dynamic epigenetic mode analysis using spatial temporal clustering |
title | Dynamic epigenetic mode analysis using spatial temporal clustering |
title_full | Dynamic epigenetic mode analysis using spatial temporal clustering |
title_fullStr | Dynamic epigenetic mode analysis using spatial temporal clustering |
title_full_unstemmed | Dynamic epigenetic mode analysis using spatial temporal clustering |
title_short | Dynamic epigenetic mode analysis using spatial temporal clustering |
title_sort | dynamic epigenetic mode analysis using spatial temporal clustering |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5259871/ https://www.ncbi.nlm.nih.gov/pubmed/28155634 http://dx.doi.org/10.1186/s12859-016-1331-z |
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