How many markers are needed to robustly determine a cell's type?

Summary: Our understanding of cell types has advanced considerably with the publication of single-cell atlases. Marker genes play an essential role for experimental validation and computational analyses such as physiological characterization, annotation, and deconvolution. However, a framework for q...

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Autores principales:	Stephan Fischer, Jesse Gillis
Formato:	article
Lenguaje:	EN
Publicado:	Elsevier 2021
Materias:	Cell biology Complex system biology Transcriptomics Science Q
Acceso en línea:	https://doaj.org/article/709b657275c74c91b0109a76b83ddabb
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spelling	oai:doaj.org-article:709b657275c74c91b0109a76b83ddabb2021-11-20T05:09:30ZHow many markers are needed to robustly determine a cell's type?2589-004210.1016/j.isci.2021.103292https://doaj.org/article/709b657275c74c91b0109a76b83ddabb2021-11-01T00:00:00Zhttp://www.sciencedirect.com/science/article/pii/S258900422101261Xhttps://doaj.org/toc/2589-0042Summary: Our understanding of cell types has advanced considerably with the publication of single-cell atlases. Marker genes play an essential role for experimental validation and computational analyses such as physiological characterization, annotation, and deconvolution. However, a framework for quantifying marker replicability and selecting replicable markers is currently lacking. Here, using high-quality data from the Brain Initiative Cell Census Network (BICCN), we systematically investigate marker replicability for 85 neuronal cell types. We show that, due to dataset-specific noise, we need to combine 5 datasets to obtain robust differentially expressed (DE) genes, particularly for rare populations and lowly expressed genes. We estimate that 10 to 200 meta-analytic markers provide optimal downstream performance and make available replicable marker lists for the 85 BICCN cell types. Replicable marker lists condense interpretable and generalizable information about cell types, opening avenues for downstream applications, including cell type annotation, selection of gene panels, and bulk data deconvolution.Stephan FischerJesse GillisElsevierarticleCell biologyComplex system biologyTranscriptomicsScienceQENiScience, Vol 24, Iss 11, Pp 103292- (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Cell biology Complex system biology Transcriptomics Science Q
spellingShingle	Cell biology Complex system biology Transcriptomics Science Q Stephan Fischer Jesse Gillis How many markers are needed to robustly determine a cell's type?
description	Summary: Our understanding of cell types has advanced considerably with the publication of single-cell atlases. Marker genes play an essential role for experimental validation and computational analyses such as physiological characterization, annotation, and deconvolution. However, a framework for quantifying marker replicability and selecting replicable markers is currently lacking. Here, using high-quality data from the Brain Initiative Cell Census Network (BICCN), we systematically investigate marker replicability for 85 neuronal cell types. We show that, due to dataset-specific noise, we need to combine 5 datasets to obtain robust differentially expressed (DE) genes, particularly for rare populations and lowly expressed genes. We estimate that 10 to 200 meta-analytic markers provide optimal downstream performance and make available replicable marker lists for the 85 BICCN cell types. Replicable marker lists condense interpretable and generalizable information about cell types, opening avenues for downstream applications, including cell type annotation, selection of gene panels, and bulk data deconvolution.
format	article
author	Stephan Fischer Jesse Gillis
author_facet	Stephan Fischer Jesse Gillis
author_sort	Stephan Fischer
title	How many markers are needed to robustly determine a cell's type?
title_short	How many markers are needed to robustly determine a cell's type?
title_full	How many markers are needed to robustly determine a cell's type?
title_fullStr	How many markers are needed to robustly determine a cell's type?
title_full_unstemmed	How many markers are needed to robustly determine a cell's type?
title_sort	how many markers are needed to robustly determine a cell's type?
publisher	Elsevier
publishDate	2021
url	https://doaj.org/article/709b657275c74c91b0109a76b83ddabb
work_keys_str_mv	AT stephanfischer howmanymarkersareneededtorobustlydetermineacellstype AT jessegillis howmanymarkersareneededtorobustlydetermineacellstype
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How many markers are needed to robustly determine a cell's type?

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