دورية أكاديمية
scMET: Bayesian modeling of DNA methylation heterogeneity at single-cell resolution.
| العنوان: | scMET: Bayesian modeling of DNA methylation heterogeneity at single-cell resolution. |
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| المؤلفون: | Kapourani CA; MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK.; School of Informatics, University of Edinburgh, Edinburgh, UK., Argelaguet R; European Bioinformatics Institute (EMBL-EBI), Hinxton, UK., Sanguinetti G; School of Informatics, University of Edinburgh, Edinburgh, UK. gsanguin@sissa.it.; SISSA, International School of Advanced Studies, Trieste, Italy. gsanguin@sissa.it., Vallejos CA; MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK. catalina.vallejos@igmm.ed.ac.uk.; The Alan Turing Institute, London, UK. catalina.vallejos@igmm.ed.ac.uk. |
| المصدر: | Genome biology [Genome Biol] 2021 Apr 20; Vol. 22 (1), pp. 114. Date of Electronic Publication: 2021 Apr 20. |
| نوع المنشور: | Journal Article; Research Support, Non-U.S. Gov't |
| اللغة: | English |
| بيانات الدورية: | Publisher: BioMed Central Ltd Country of Publication: England NLM ID: 100960660 Publication Model: Electronic Cited Medium: Internet ISSN: 1474-760X (Electronic) Linking ISSN: 14747596 NLM ISO Abbreviation: Genome Biol Subsets: MEDLINE |
| أسماء مطبوعة: | Publication: London, UK : BioMed Central Ltd Original Publication: London : Genome Biology Ltd., c2000- |
| مواضيع طبية MeSH: | Bayes Theorem* , DNA Methylation* , Epigenesis, Genetic* , Genetic Heterogeneity* , Software*, Epigenomics/*methods , Single-Cell Analysis/*methods, Algorithms ; Computational Biology/methods |
| مستخلص: | High-throughput single-cell measurements of DNA methylomes can quantify methylation heterogeneity and uncover its role in gene regulation. However, technical limitations and sparse coverage can preclude this task. scMET is a hierarchical Bayesian model which overcomes sparsity, sharing information across cells and genomic features to robustly quantify genuine biological heterogeneity. scMET can identify highly variable features that drive epigenetic heterogeneity, and perform differential methylation and variability analyses. We illustrate how scMET facilitates the characterization of epigenetically distinct cell populations and how it enables the formulation of novel hypotheses on the epigenetic regulation of gene expression. scMET is available at https://github.com/andreaskapou/scMET . |
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| معلومات مُعتمدة: | MC_UU_00009/2 United Kingdom MRC_ Medical Research Council |
| فهرسة مساهمة: | Keywords: DNA methylation; Epigenetic heterogeneity; Hierarchical Bayes; Single-cell |
| تواريخ الأحداث: | Date Created: 20210421 Date Completed: 20220114 Latest Revision: 20231101 |
| رمز التحديث: | 20240628 |
| مُعرف محوري في PubMed: | PMC8056718 |
| DOI: | 10.1186/s13059-021-02329-8 |
| PMID: | 33879195 |
| قاعدة البيانات: | MEDLINE |
Find this article in full text from Springer Verlag. 
Full Text Finder | تدمد: | 1474-760X |
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| DOI: | 10.1186/s13059-021-02329-8 |