Cell type and gene expression deconvolution with BayesPrism enables Bayesian integrative analysis across bulk and single-cell RNA sequencing in oncology

Inferring single-cell compositions and their contributions to global gene expression changes from bulk RNA sequencing (RNA-seq) datasets is a major challenge in oncology. Here we develop Bayesian cell proportion reconstruction inferred using statistical marginalization (BayesPrism), a Bayesian metho...

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Detalles Bibliográficos
Autores principales: Chu, Tinyi, Wang, Zhong, Pe’er, Dana, Danko, Charles G.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group US 2022
Materias:
Technical Report
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9046084/
https://www.ncbi.nlm.nih.gov/pubmed/35469013
http://dx.doi.org/10.1038/s43018-022-00356-3

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9046084/
https://www.ncbi.nlm.nih.gov/pubmed/35469013
http://dx.doi.org/10.1038/s43018-022-00356-3

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