Comparison of bias and resolvability in single-cell and single-transcript methods

Rammohan et al. propose a generalizable framework for performing multiple methods in parallel using split samples, so that experimental variability is defined and compared between methods. Their framework provides a practical solution for benchmarking and comparing the performance of any method, ill...

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Autores principales:	Jayan Rammohan, Steven P. Lund, Nina Alperovich, Vanya Paralanov, Elizabeth A. Strychalski, David Ross
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Biology (General) QH301-705.5
Acceso en línea:	https://doaj.org/article/18b4195254e744b8911081408a581ce2
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spelling	oai:doaj.org-article:18b4195254e744b8911081408a581ce22021-12-02T15:56:49ZComparison of bias and resolvability in single-cell and single-transcript methods10.1038/s42003-021-02138-62399-3642https://doaj.org/article/18b4195254e744b8911081408a581ce22021-06-01T00:00:00Zhttps://doi.org/10.1038/s42003-021-02138-6https://doaj.org/toc/2399-3642Rammohan et al. propose a generalizable framework for performing multiple methods in parallel using split samples, so that experimental variability is defined and compared between methods. Their framework provides a practical solution for benchmarking and comparing the performance of any method, illustrated by analysing single-cell and single-transcript methods.Jayan RammohanSteven P. LundNina AlperovichVanya ParalanovElizabeth A. StrychalskiDavid RossNature PortfolioarticleBiology (General)QH301-705.5ENCommunications Biology, Vol 4, Iss 1, Pp 1-14 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Biology (General) QH301-705.5
spellingShingle	Biology (General) QH301-705.5 Jayan Rammohan Steven P. Lund Nina Alperovich Vanya Paralanov Elizabeth A. Strychalski David Ross Comparison of bias and resolvability in single-cell and single-transcript methods
description	Rammohan et al. propose a generalizable framework for performing multiple methods in parallel using split samples, so that experimental variability is defined and compared between methods. Their framework provides a practical solution for benchmarking and comparing the performance of any method, illustrated by analysing single-cell and single-transcript methods.
format	article
author	Jayan Rammohan Steven P. Lund Nina Alperovich Vanya Paralanov Elizabeth A. Strychalski David Ross
author_facet	Jayan Rammohan Steven P. Lund Nina Alperovich Vanya Paralanov Elizabeth A. Strychalski David Ross
author_sort	Jayan Rammohan
title	Comparison of bias and resolvability in single-cell and single-transcript methods
title_short	Comparison of bias and resolvability in single-cell and single-transcript methods
title_full	Comparison of bias and resolvability in single-cell and single-transcript methods
title_fullStr	Comparison of bias and resolvability in single-cell and single-transcript methods
title_full_unstemmed	Comparison of bias and resolvability in single-cell and single-transcript methods
title_sort	comparison of bias and resolvability in single-cell and single-transcript methods
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/18b4195254e744b8911081408a581ce2
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Comparison of bias and resolvability in single-cell and single-transcript methods

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