GapClust is a light-weight approach distinguishing rare cells from voluminous single cell expression profiles

While rare cell type identification is indispensable in single cell studies, powerful tools with high detection accuracy and computational efficiency are still lacking. Here, the authors propose a light-weight algorithm which can distinguish rare cell types from voluminous single cell expression pro...

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Autores principales:	Botao Fa, Ting Wei, Yuan Zhou, Luke Johnston, Xin Yuan, Yanran Ma, Yue Zhang, Zhangsheng Yu
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Science Q
Acceso en línea:	https://doaj.org/article/8ade08b8a643414e84ebe9771752ced7
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spelling	oai:doaj.org-article:8ade08b8a643414e84ebe9771752ced72021-12-02T15:23:18ZGapClust is a light-weight approach distinguishing rare cells from voluminous single cell expression profiles10.1038/s41467-021-24489-82041-1723https://doaj.org/article/8ade08b8a643414e84ebe9771752ced72021-07-01T00:00:00Zhttps://doi.org/10.1038/s41467-021-24489-8https://doaj.org/toc/2041-1723While rare cell type identification is indispensable in single cell studies, powerful tools with high detection accuracy and computational efficiency are still lacking. Here, the authors propose a light-weight algorithm which can distinguish rare cell types from voluminous single cell expression profiles.Botao FaTing WeiYuan ZhouLuke JohnstonXin YuanYanran MaYue ZhangZhangsheng YuNature PortfolioarticleScienceQENNature Communications, Vol 12, Iss 1, Pp 1-11 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Science Q
spellingShingle	Science Q Botao Fa Ting Wei Yuan Zhou Luke Johnston Xin Yuan Yanran Ma Yue Zhang Zhangsheng Yu GapClust is a light-weight approach distinguishing rare cells from voluminous single cell expression profiles
description	While rare cell type identification is indispensable in single cell studies, powerful tools with high detection accuracy and computational efficiency are still lacking. Here, the authors propose a light-weight algorithm which can distinguish rare cell types from voluminous single cell expression profiles.
format	article
author	Botao Fa Ting Wei Yuan Zhou Luke Johnston Xin Yuan Yanran Ma Yue Zhang Zhangsheng Yu
author_facet	Botao Fa Ting Wei Yuan Zhou Luke Johnston Xin Yuan Yanran Ma Yue Zhang Zhangsheng Yu
author_sort	Botao Fa
title	GapClust is a light-weight approach distinguishing rare cells from voluminous single cell expression profiles
title_short	GapClust is a light-weight approach distinguishing rare cells from voluminous single cell expression profiles
title_full	GapClust is a light-weight approach distinguishing rare cells from voluminous single cell expression profiles
title_fullStr	GapClust is a light-weight approach distinguishing rare cells from voluminous single cell expression profiles
title_full_unstemmed	GapClust is a light-weight approach distinguishing rare cells from voluminous single cell expression profiles
title_sort	gapclust is a light-weight approach distinguishing rare cells from voluminous single cell expression profiles
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/8ade08b8a643414e84ebe9771752ced7
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GapClust is a light-weight approach distinguishing rare cells from voluminous single cell expression profiles

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