Identifying topologically associating domains and subdomains by Gaussian Mixture model And Proportion test
Spatial organization of the genome plays a crucial role in regulating gene expression. Here the authors introduce GMAP, the Gaussian Mixture model And Proportion test, to identify topologically associating domains and subdomains in Hi-C data.
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| Format: | Article |
| Language: | English |
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Nature Publishing Group
2017-09-01
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| Series: | Nature Communications |
| Online Access: | https://doi.org/10.1038/s41467-017-00478-8 |
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doaj-324439f719804898a27e1bc7c4641b2d |
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Article |
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doaj-324439f719804898a27e1bc7c4641b2d2021-05-11T07:21:02ZengNature Publishing GroupNature Communications2041-17232017-09-01811910.1038/s41467-017-00478-8Identifying topologically associating domains and subdomains by Gaussian Mixture model And Proportion testWenbao Yu0Bing He1Kai Tan2Department of Biomedical and Health Informatics, Children’s Hospital of PhiladelphiaDepartment of Biomedical and Health Informatics, Children’s Hospital of PhiladelphiaDepartment of Biomedical and Health Informatics, Children’s Hospital of PhiladelphiaSpatial organization of the genome plays a crucial role in regulating gene expression. Here the authors introduce GMAP, the Gaussian Mixture model And Proportion test, to identify topologically associating domains and subdomains in Hi-C data.https://doi.org/10.1038/s41467-017-00478-8 |
| collection |
DOAJ |
| language |
English |
| format |
Article |
| sources |
DOAJ |
| author |
Wenbao Yu Bing He Kai Tan |
| spellingShingle |
Wenbao Yu Bing He Kai Tan Identifying topologically associating domains and subdomains by Gaussian Mixture model And Proportion test Nature Communications |
| author_facet |
Wenbao Yu Bing He Kai Tan |
| author_sort |
Wenbao Yu |
| title |
Identifying topologically associating domains and subdomains by Gaussian Mixture model And Proportion test |
| title_short |
Identifying topologically associating domains and subdomains by Gaussian Mixture model And Proportion test |
| title_full |
Identifying topologically associating domains and subdomains by Gaussian Mixture model And Proportion test |
| title_fullStr |
Identifying topologically associating domains and subdomains by Gaussian Mixture model And Proportion test |
| title_full_unstemmed |
Identifying topologically associating domains and subdomains by Gaussian Mixture model And Proportion test |
| title_sort |
identifying topologically associating domains and subdomains by gaussian mixture model and proportion test |
| publisher |
Nature Publishing Group |
| series |
Nature Communications |
| issn |
2041-1723 |
| publishDate |
2017-09-01 |
| description |
Spatial organization of the genome plays a crucial role in regulating gene expression. Here the authors introduce GMAP, the Gaussian Mixture model And Proportion test, to identify topologically associating domains and subdomains in Hi-C data. |
| url |
https://doi.org/10.1038/s41467-017-00478-8 |
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