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

Research output: Contribution to journalArticlepeer-review

Abstract

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.

Original languageEnglish (US)
Article number371
JournalBMC genomics
Volume24
Issue number1
DOIs
StatePublished - Dec 2023
Externally publishedYes

Keywords

  • Gene expression
  • RNA-seq
  • Single cell
  • Stem cell

ASJC Scopus subject areas

  • Biotechnology
  • Genetics

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