Cargando…
scMET: Bayesian modeling of DNA methylation heterogeneity at single-cell resolution
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 a...
Autores principales: | Kapourani, Chantriolnt-Andreas, Argelaguet, Ricard, Sanguinetti, Guido, Vallejos, Catalina A. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8056718/ https://www.ncbi.nlm.nih.gov/pubmed/33879195 http://dx.doi.org/10.1186/s13059-021-02329-8 |
Ejemplares similares
-
Melissa: Bayesian clustering and imputation of single-cell methylomes
por: Kapourani, Chantriolnt-Andreas, et al.
Publicado: (2019) -
scNMT-seq enables joint profiling of chromatin accessibility DNA methylation and transcription in single cells
por: Clark, Stephen J., et al.
Publicado: (2018) -
BPRMeth: a flexible Bioconductor package for modelling methylation profiles
por: Kapourani, Chantriolnt-Andreas, et al.
Publicado: (2018) -
Multi-omics profiling of mouse gastrulation at single cell resolution
por: Argelaguet, Ricard, et al.
Publicado: (2019) -
SCRaPL: A Bayesian hierarchical framework for detecting technical associates in single cell multiomics data
por: Maniatis, Christos, et al.
Publicado: (2022)