TCM visualizes trajectories and cell populations from single cell data

Time series single cell expression data has large variance between time points and is challenging for analysis. Here, the authors develop a new dimension reduction and data visualization tool for large scale temporal scRNA-seq data which identifies trajectories and subpopulations.

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Autores principales:	Wuming Gong, Il-Youp Kwak, Naoko Koyano-Nakagawa, Wei Pan, Daniel J. Garry
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2018
Materias:	Science Q
Acceso en línea:	https://doaj.org/article/3107b11735c5411d8a8c981b9ffc4189
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:3107b11735c5411d8a8c981b9ffc4189
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spelling	oai:doaj.org-article:3107b11735c5411d8a8c981b9ffc41892021-12-02T15:34:39ZTCM visualizes trajectories and cell populations from single cell data10.1038/s41467-018-05112-92041-1723https://doaj.org/article/3107b11735c5411d8a8c981b9ffc41892018-07-01T00:00:00Zhttps://doi.org/10.1038/s41467-018-05112-9https://doaj.org/toc/2041-1723Time series single cell expression data has large variance between time points and is challenging for analysis. Here, the authors develop a new dimension reduction and data visualization tool for large scale temporal scRNA-seq data which identifies trajectories and subpopulations.Wuming GongIl-Youp KwakNaoko Koyano-NakagawaWei PanDaniel J. GarryNature PortfolioarticleScienceQENNature Communications, Vol 9, Iss 1, Pp 1-8 (2018)
institution	DOAJ
collection	DOAJ
language	EN
topic	Science Q
spellingShingle	Science Q Wuming Gong Il-Youp Kwak Naoko Koyano-Nakagawa Wei Pan Daniel J. Garry TCM visualizes trajectories and cell populations from single cell data
description	Time series single cell expression data has large variance between time points and is challenging for analysis. Here, the authors develop a new dimension reduction and data visualization tool for large scale temporal scRNA-seq data which identifies trajectories and subpopulations.
format	article
author	Wuming Gong Il-Youp Kwak Naoko Koyano-Nakagawa Wei Pan Daniel J. Garry
author_facet	Wuming Gong Il-Youp Kwak Naoko Koyano-Nakagawa Wei Pan Daniel J. Garry
author_sort	Wuming Gong
title	TCM visualizes trajectories and cell populations from single cell data
title_short	TCM visualizes trajectories and cell populations from single cell data
title_full	TCM visualizes trajectories and cell populations from single cell data
title_fullStr	TCM visualizes trajectories and cell populations from single cell data
title_full_unstemmed	TCM visualizes trajectories and cell populations from single cell data
title_sort	tcm visualizes trajectories and cell populations from single cell data
publisher	Nature Portfolio
publishDate	2018
url	https://doaj.org/article/3107b11735c5411d8a8c981b9ffc4189
work_keys_str_mv	AT wuminggong tcmvisualizestrajectoriesandcellpopulationsfromsinglecelldata AT ilyoupkwak tcmvisualizestrajectoriesandcellpopulationsfromsinglecelldata AT naokokoyanonakagawa tcmvisualizestrajectoriesandcellpopulationsfromsinglecelldata AT weipan tcmvisualizestrajectoriesandcellpopulationsfromsinglecelldata AT danieljgarry tcmvisualizestrajectoriesandcellpopulationsfromsinglecelldata
_version_	1718386772979744768

TCM visualizes trajectories and cell populations from single cell data

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