Automated methods for cell type annotation on scRNA-seq data
The advent of single-cell sequencing started a new era of transcriptomic and genomic research, advancing our knowledge of the cellular heterogeneity and dynamics. Cell type annotation is a crucial step in analyzing single-cell RNA sequencing data, yet manual annotation is time-consuming and partiall...
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doaj-72c1e9c5fdbc4df8b56b7a5da34954962021-02-05T15:30:42ZengElsevierComputational and Structural Biotechnology Journal2001-03702021-01-0119961969Automated methods for cell type annotation on scRNA-seq dataGiovanni Pasquini0Jesus Eduardo Rojo Arias1Patrick Schäfer2Volker Busskamp3Technische Universität Dresden, Center for Molecular and Cellular Bioengineering (CMCB), Center for Regenerative Therapies Dresden (CRTD), Dresden 01307, Germany; Universitäts-Augenklinik Bonn, University of Bonn, Department of Ophthalmology, Bonn 53127, GermanyWellcome-MRC Cambridge Stem Cell Institute, Jeffrey Cheah Biomedical Centre, Cambridge Biomedical Campus, University of Cambridge, Cambridge, UKTechnische Universität Dresden, Center for Molecular and Cellular Bioengineering (CMCB), Center for Regenerative Therapies Dresden (CRTD), Dresden 01307, GermanyTechnische Universität Dresden, Center for Molecular and Cellular Bioengineering (CMCB), Center for Regenerative Therapies Dresden (CRTD), Dresden 01307, Germany; Universitäts-Augenklinik Bonn, University of Bonn, Department of Ophthalmology, Bonn 53127, Germany; Corresponding author at: Universitäts-Augenklinik Bonn, University of Bonn, Department of Ophthalmology, Bonn 53127, Germany.The advent of single-cell sequencing started a new era of transcriptomic and genomic research, advancing our knowledge of the cellular heterogeneity and dynamics. Cell type annotation is a crucial step in analyzing single-cell RNA sequencing data, yet manual annotation is time-consuming and partially subjective. As an alternative, tools have been developed for automatic cell type identification. Different strategies have emerged to ultimately associate gene expression profiles of single cells with a cell type either by using curated marker gene databases, correlating reference expression data, or transferring labels by supervised classification. In this review, we present an overview of the available tools and the underlying approaches to perform automated cell type annotations on scRNA-seq data.http://www.sciencedirect.com/science/article/pii/S2001037021000192scRNA-seqCell typeCell stateAutomatic annotation |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Giovanni Pasquini Jesus Eduardo Rojo Arias Patrick Schäfer Volker Busskamp |
spellingShingle |
Giovanni Pasquini Jesus Eduardo Rojo Arias Patrick Schäfer Volker Busskamp Automated methods for cell type annotation on scRNA-seq data Computational and Structural Biotechnology Journal scRNA-seq Cell type Cell state Automatic annotation |
author_facet |
Giovanni Pasquini Jesus Eduardo Rojo Arias Patrick Schäfer Volker Busskamp |
author_sort |
Giovanni Pasquini |
title |
Automated methods for cell type annotation on scRNA-seq data |
title_short |
Automated methods for cell type annotation on scRNA-seq data |
title_full |
Automated methods for cell type annotation on scRNA-seq data |
title_fullStr |
Automated methods for cell type annotation on scRNA-seq data |
title_full_unstemmed |
Automated methods for cell type annotation on scRNA-seq data |
title_sort |
automated methods for cell type annotation on scrna-seq data |
publisher |
Elsevier |
series |
Computational and Structural Biotechnology Journal |
issn |
2001-0370 |
publishDate |
2021-01-01 |
description |
The advent of single-cell sequencing started a new era of transcriptomic and genomic research, advancing our knowledge of the cellular heterogeneity and dynamics. Cell type annotation is a crucial step in analyzing single-cell RNA sequencing data, yet manual annotation is time-consuming and partially subjective. As an alternative, tools have been developed for automatic cell type identification. Different strategies have emerged to ultimately associate gene expression profiles of single cells with a cell type either by using curated marker gene databases, correlating reference expression data, or transferring labels by supervised classification. In this review, we present an overview of the available tools and the underlying approaches to perform automated cell type annotations on scRNA-seq data. |
topic |
scRNA-seq Cell type Cell state Automatic annotation |
url |
http://www.sciencedirect.com/science/article/pii/S2001037021000192 |
work_keys_str_mv |
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