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JMG, Humans, Gene Expression Profiling, Single-Cell Gene Expression Analysis, Induced Pluripotent Stem Cells, RNA-Seq, Single-Cell Analysis, Sequence Analysis, RNA

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BMC Genomics. 2023;24(1):371.







This work was supported by National Institutes of Health grant HL149620, DK129964, and the Advancing a Healthier Wisconsin Endowment.


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.


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