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Robustness of single-cell RNA-seq for identifying differentially expressed genes

BACKGROUND: A common feature of single-cell RNA-seq (scRNA-seq) data is that the number of cells in a cell cluster may vary widely, ranging from a few dozen to several thousand. It is not clear whether scRNA-seq data from a small number of cells allow robust identification of differentially expresse...

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Autores principales: Liu, Yong, Huang, Jing, Pandey, Rajan, Liu, Pengyuan, Therani, Bhavika, Qiu, Qiongzi, Rao, Sridhar, Geurts, Aron M., Cowley, Allen W., Greene, Andrew S., Liang, Mingyu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10316566/
https://www.ncbi.nlm.nih.gov/pubmed/37394518
http://dx.doi.org/10.1186/s12864-023-09487-y
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author Liu, Yong
Huang, Jing
Pandey, Rajan
Liu, Pengyuan
Therani, Bhavika
Qiu, Qiongzi
Rao, Sridhar
Geurts, Aron M.
Cowley, Allen W.
Greene, Andrew S.
Liang, Mingyu
author_facet Liu, Yong
Huang, Jing
Pandey, Rajan
Liu, Pengyuan
Therani, Bhavika
Qiu, Qiongzi
Rao, Sridhar
Geurts, Aron M.
Cowley, Allen W.
Greene, Andrew S.
Liang, Mingyu
author_sort Liu, Yong
collection PubMed
description BACKGROUND: A common feature of single-cell RNA-seq (scRNA-seq) data is that the number of cells in a cell cluster may vary widely, ranging from a few dozen to several thousand. It is not clear whether scRNA-seq data from a small number of cells allow robust identification of differentially expressed genes (DEGs) with various characteristics. RESULTS: We addressed this question by performing scRNA-seq and poly(A)-dependent bulk RNA-seq in comparable aliquots of human induced pluripotent stem cells-derived, purified vascular endothelial and smooth muscle cells. We found that scRNA-seq data needed to have 2,000 or more cells in a cluster to identify the majority of DEGs that would show modest differences in a bulk RNA-seq analysis. On the other hand, clusters with as few as 50–100 cells may be sufficient for identifying the majority of DEGs that would have extremely small p values or transcript abundance greater than a few hundred transcripts per million in a bulk RNA-seq analysis. CONCLUSION: Findings of the current study provide a quantitative reference for designing studies that aim for identifying DEGs for specific cell clusters using scRNA-seq data and for interpreting results of such studies. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12864-023-09487-y.
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spelling pubmed-103165662023-07-04 Robustness of single-cell RNA-seq for identifying differentially expressed genes Liu, Yong Huang, Jing Pandey, Rajan Liu, Pengyuan Therani, Bhavika Qiu, Qiongzi Rao, Sridhar Geurts, Aron M. Cowley, Allen W. Greene, Andrew S. Liang, Mingyu BMC Genomics Research BACKGROUND: A common feature of single-cell RNA-seq (scRNA-seq) data is that the number of cells in a cell cluster may vary widely, ranging from a few dozen to several thousand. It is not clear whether scRNA-seq data from a small number of cells allow robust identification of differentially expressed genes (DEGs) with various characteristics. RESULTS: We addressed this question by performing scRNA-seq and poly(A)-dependent bulk RNA-seq in comparable aliquots of human induced pluripotent stem cells-derived, purified vascular endothelial and smooth muscle cells. We found that scRNA-seq data needed to have 2,000 or more cells in a cluster to identify the majority of DEGs that would show modest differences in a bulk RNA-seq analysis. On the other hand, clusters with as few as 50–100 cells may be sufficient for identifying the majority of DEGs that would have extremely small p values or transcript abundance greater than a few hundred transcripts per million in a bulk RNA-seq analysis. CONCLUSION: Findings of the current study provide a quantitative reference for designing studies that aim for identifying DEGs for specific cell clusters using scRNA-seq data and for interpreting results of such studies. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12864-023-09487-y. BioMed Central 2023-07-03 /pmc/articles/PMC10316566/ /pubmed/37394518 http://dx.doi.org/10.1186/s12864-023-09487-y Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Liu, Yong
Huang, Jing
Pandey, Rajan
Liu, Pengyuan
Therani, Bhavika
Qiu, Qiongzi
Rao, Sridhar
Geurts, Aron M.
Cowley, Allen W.
Greene, Andrew S.
Liang, Mingyu
Robustness of single-cell RNA-seq for identifying differentially expressed genes
title Robustness of single-cell RNA-seq for identifying differentially expressed genes
title_full Robustness of single-cell RNA-seq for identifying differentially expressed genes
title_fullStr Robustness of single-cell RNA-seq for identifying differentially expressed genes
title_full_unstemmed Robustness of single-cell RNA-seq for identifying differentially expressed genes
title_short Robustness of single-cell RNA-seq for identifying differentially expressed genes
title_sort robustness of single-cell rna-seq for identifying differentially expressed genes
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10316566/
https://www.ncbi.nlm.nih.gov/pubmed/37394518
http://dx.doi.org/10.1186/s12864-023-09487-y
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