Sensitive detection of rare disease-associated cell subsets via representation learning

While rare cell subpopulations frequently make the difference between health and disease, their detection remains a challenge. Here, the authors devise CellCnn, a representation learning approach to detecting such rare cell populations from high-dimensional single cell data, and, among other example...

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Autores principales:	Eirini Arvaniti, Manfred Claassen
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2017
Materias:	Science Q
Acceso en línea:	https://doaj.org/article/252419b4dcba439fba6a1a58ee8e5a66
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spelling	oai:doaj.org-article:252419b4dcba439fba6a1a58ee8e5a662021-12-02T14:42:51ZSensitive detection of rare disease-associated cell subsets via representation learning10.1038/ncomms148252041-1723https://doaj.org/article/252419b4dcba439fba6a1a58ee8e5a662017-04-01T00:00:00Zhttps://doi.org/10.1038/ncomms14825https://doaj.org/toc/2041-1723While rare cell subpopulations frequently make the difference between health and disease, their detection remains a challenge. Here, the authors devise CellCnn, a representation learning approach to detecting such rare cell populations from high-dimensional single cell data, and, among other examples, demonstrate its capacity for detecting rare leukaemic blasts in minimal residual disease.Eirini ArvanitiManfred ClaassenNature PortfolioarticleScienceQENNature Communications, Vol 8, Iss 1, Pp 1-10 (2017)
institution	DOAJ
collection	DOAJ
language	EN
topic	Science Q
spellingShingle	Science Q Eirini Arvaniti Manfred Claassen Sensitive detection of rare disease-associated cell subsets via representation learning
description	While rare cell subpopulations frequently make the difference between health and disease, their detection remains a challenge. Here, the authors devise CellCnn, a representation learning approach to detecting such rare cell populations from high-dimensional single cell data, and, among other examples, demonstrate its capacity for detecting rare leukaemic blasts in minimal residual disease.
format	article
author	Eirini Arvaniti Manfred Claassen
author_facet	Eirini Arvaniti Manfred Claassen
author_sort	Eirini Arvaniti
title	Sensitive detection of rare disease-associated cell subsets via representation learning
title_short	Sensitive detection of rare disease-associated cell subsets via representation learning
title_full	Sensitive detection of rare disease-associated cell subsets via representation learning
title_fullStr	Sensitive detection of rare disease-associated cell subsets via representation learning
title_full_unstemmed	Sensitive detection of rare disease-associated cell subsets via representation learning
title_sort	sensitive detection of rare disease-associated cell subsets via representation learning
publisher	Nature Portfolio
publishDate	2017
url	https://doaj.org/article/252419b4dcba439fba6a1a58ee8e5a66
work_keys_str_mv	AT eiriniarvaniti sensitivedetectionofrarediseaseassociatedcellsubsetsviarepresentationlearning AT manfredclaassen sensitivedetectionofrarediseaseassociatedcellsubsetsviarepresentationlearning
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Sensitive detection of rare disease-associated cell subsets via representation learning

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