Deep generative model embedding of single-cell RNA-Seq profiles on hyperspheres and hyperbolic spaces

Single-cell RNA-seq allows the study of tissues at cellular resolution. Here, the authors demonstrate how deep learning can be used to gain biological insight from such data by accounting for biological and technical variability. Data exploration is improved by accurately visualizing cells on an int...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Jiarui Ding, Aviv Regev
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Science Q
Acceso en línea:	https://doaj.org/article/050105f7e38d42cba8c66492f371e672
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:050105f7e38d42cba8c66492f371e672
record_format	dspace
spelling	oai:doaj.org-article:050105f7e38d42cba8c66492f371e6722021-12-02T16:49:12ZDeep generative model embedding of single-cell RNA-Seq profiles on hyperspheres and hyperbolic spaces10.1038/s41467-021-22851-42041-1723https://doaj.org/article/050105f7e38d42cba8c66492f371e6722021-05-01T00:00:00Zhttps://doi.org/10.1038/s41467-021-22851-4https://doaj.org/toc/2041-1723Single-cell RNA-seq allows the study of tissues at cellular resolution. Here, the authors demonstrate how deep learning can be used to gain biological insight from such data by accounting for biological and technical variability. Data exploration is improved by accurately visualizing cells on an interactive 3D surface.Jiarui DingAviv RegevNature PortfolioarticleScienceQENNature Communications, Vol 12, Iss 1, Pp 1-17 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Science Q
spellingShingle	Science Q Jiarui Ding Aviv Regev Deep generative model embedding of single-cell RNA-Seq profiles on hyperspheres and hyperbolic spaces
description	Single-cell RNA-seq allows the study of tissues at cellular resolution. Here, the authors demonstrate how deep learning can be used to gain biological insight from such data by accounting for biological and technical variability. Data exploration is improved by accurately visualizing cells on an interactive 3D surface.
format	article
author	Jiarui Ding Aviv Regev
author_facet	Jiarui Ding Aviv Regev
author_sort	Jiarui Ding
title	Deep generative model embedding of single-cell RNA-Seq profiles on hyperspheres and hyperbolic spaces
title_short	Deep generative model embedding of single-cell RNA-Seq profiles on hyperspheres and hyperbolic spaces
title_full	Deep generative model embedding of single-cell RNA-Seq profiles on hyperspheres and hyperbolic spaces
title_fullStr	Deep generative model embedding of single-cell RNA-Seq profiles on hyperspheres and hyperbolic spaces
title_full_unstemmed	Deep generative model embedding of single-cell RNA-Seq profiles on hyperspheres and hyperbolic spaces
title_sort	deep generative model embedding of single-cell rna-seq profiles on hyperspheres and hyperbolic spaces
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/050105f7e38d42cba8c66492f371e672
work_keys_str_mv	AT jiaruiding deepgenerativemodelembeddingofsinglecellrnaseqprofilesonhyperspheresandhyperbolicspaces AT avivregev deepgenerativemodelembeddingofsinglecellrnaseqprofilesonhyperspheresandhyperbolicspaces
_version_	1718383375815802880

Deep generative model embedding of single-cell RNA-Seq profiles on hyperspheres and hyperbolic spaces

Ejemplares similares