A balanced measure shows superior performance of pseudobulk methods in single-cell RNA-sequencing analysis
Published in Nature Communications, 2022
Recently, Zimmerman et al., highlighted the importance of accounting for the dependence between cells from the same individual when conducting differential expression analysis on single-cell RNA-sequencing data. Their work proved the inadequacy of pseudoreplication approaches for such analysis — this was an important step forward that was conclusively proven by them. However, there appear to be limitations in both their benchmarking and simulation approaches. Here, we corrected these issues, reran the author’s analysis and found that pseudobulk methods outperformed mixed models. Based on these findings, we recommend the use of pseudobulk approaches for differential expression in single-cell RNA-sequencing analyses.
Recommended citation: Murphy, A. E. & Skene, N. G. Nat. Commun. 37, 7851 (2022).
Recommended citation: Murphy, A. E. & Skene, N. G. Nat. Commun. 37, 7851 (2022)
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