1. Robustness of single-cell RNA-seq for identifying differentially expressed genes
- Author
-
Yong Liu, Jing Huang, Rajan Pandey, Pengyuan Liu, Bhavika Therani, Qiongzi Qiu, Sridhar Rao, Aron M. Geurts, Allen W. Cowley, Andrew S. Greene, and Mingyu Liang
- Subjects
RNA-seq ,Gene expression ,Stem cell ,Single cell ,Biotechnology ,TP248.13-248.65 ,Genetics ,QH426-470 - Abstract
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.
- Published
- 2023
- Full Text
- View/download PDF