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

Area of Science:

• Genomics
• Molecular Biology
• Bioinformatics

Background:

• Single-cell RNA sequencing (scRNA-seq) data often exhibit wide cell cluster size variations.
• The reliability of identifying differentially expressed genes (DEGs) from small cell clusters in scRNA-seq is not well-established.

Purpose of the Study:

• To determine the minimum number of cells required in scRNA-seq clusters for robust DEG identification.
• To provide quantitative guidance for designing and interpreting scRNA-seq studies.

Main Methods:

• Comparative analysis of scRNA-seq and poly(A)-dependent bulk RNA sequencing.
• Utilized human induced pluripotent stem cells-derived vascular endothelial and smooth muscle cells.

Main Results:

• scRNA-seq clusters need ≥2,000 cells to identify most DEGs with modest differences compared to bulk RNA-seq.
• Clusters with 50-100 cells can identify DEGs with very small p-values or high transcript abundance (>few hundred transcripts per million).

Conclusions:

• Offers a quantitative reference for scRNA-seq study design and DEG identification in cell clusters.
• Informs researchers on cell number requirements for detecting DEGs with varying characteristics.