AutoSpill is a principled framework that simplifies the analysis of multichromatic flow cytometry data

Flow cytometry allows the simultaneous quantification of many markers in and on a cell, but the analysis of such data is complicated. Here, the authors propose AutoSpill, a framework that facilitates the analysis of such data by automating parts of the analysis and requiring fewer controls.

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Autores principales:	Carlos P. Roca, Oliver T. Burton, Václav Gergelits, Teresa Prezzemolo, Carly E. Whyte, Richard Halpert, Łukasz Kreft, James Collier, Alexander Botzki, Josef Spidlen, Stéphanie Humblet-Baron, Adrian Liston
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Science Q
Acceso en línea:	https://doaj.org/article/6c6ef8a9653a48cd8a83f09749fed584
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spelling	oai:doaj.org-article:6c6ef8a9653a48cd8a83f09749fed5842021-12-02T15:45:13ZAutoSpill is a principled framework that simplifies the analysis of multichromatic flow cytometry data10.1038/s41467-021-23126-82041-1723https://doaj.org/article/6c6ef8a9653a48cd8a83f09749fed5842021-05-01T00:00:00Zhttps://doi.org/10.1038/s41467-021-23126-8https://doaj.org/toc/2041-1723Flow cytometry allows the simultaneous quantification of many markers in and on a cell, but the analysis of such data is complicated. Here, the authors propose AutoSpill, a framework that facilitates the analysis of such data by automating parts of the analysis and requiring fewer controls.Carlos P. RocaOliver T. BurtonVáclav GergelitsTeresa PrezzemoloCarly E. WhyteRichard HalpertŁukasz KreftJames CollierAlexander BotzkiJosef SpidlenStéphanie Humblet-BaronAdrian ListonNature PortfolioarticleScienceQENNature Communications, Vol 12, Iss 1, Pp 1-16 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Science Q
spellingShingle	Science Q Carlos P. Roca Oliver T. Burton Václav Gergelits Teresa Prezzemolo Carly E. Whyte Richard Halpert Łukasz Kreft James Collier Alexander Botzki Josef Spidlen Stéphanie Humblet-Baron Adrian Liston AutoSpill is a principled framework that simplifies the analysis of multichromatic flow cytometry data
description	Flow cytometry allows the simultaneous quantification of many markers in and on a cell, but the analysis of such data is complicated. Here, the authors propose AutoSpill, a framework that facilitates the analysis of such data by automating parts of the analysis and requiring fewer controls.
format	article
author	Carlos P. Roca Oliver T. Burton Václav Gergelits Teresa Prezzemolo Carly E. Whyte Richard Halpert Łukasz Kreft James Collier Alexander Botzki Josef Spidlen Stéphanie Humblet-Baron Adrian Liston
author_facet	Carlos P. Roca Oliver T. Burton Václav Gergelits Teresa Prezzemolo Carly E. Whyte Richard Halpert Łukasz Kreft James Collier Alexander Botzki Josef Spidlen Stéphanie Humblet-Baron Adrian Liston
author_sort	Carlos P. Roca
title	AutoSpill is a principled framework that simplifies the analysis of multichromatic flow cytometry data
title_short	AutoSpill is a principled framework that simplifies the analysis of multichromatic flow cytometry data
title_full	AutoSpill is a principled framework that simplifies the analysis of multichromatic flow cytometry data
title_fullStr	AutoSpill is a principled framework that simplifies the analysis of multichromatic flow cytometry data
title_full_unstemmed	AutoSpill is a principled framework that simplifies the analysis of multichromatic flow cytometry data
title_sort	autospill is a principled framework that simplifies the analysis of multichromatic flow cytometry data
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/6c6ef8a9653a48cd8a83f09749fed584
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AutoSpill is a principled framework that simplifies the analysis of multichromatic flow cytometry data

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