Avoiding false discoveries: Revisiting an Alzheimer’s disease snRNA-Seq dataset

Mathys et al ., conducted the first single-nucleus RNA-Seq study (snRNA-Seq) of Alzheimer’s disease (AD) 1 . The authors profiled the transcriptomes of approximately 80,000 cells from the prefrontal cortex, collected from 48 individuals – 24 of which presented with varying degrees of AD pathology. With bulk RNA-Seq, changes in gene expression across cell types can be lost, potentially masking the differentially expressed genes (DEGs) across different cell types. Through the use of single-cell techniques, the authors benefitted from increased resolution with the potential to uncover cell type-specific DEGs in AD for the first time 2 . However, there were limitations in both their data processing and quality control and their differential expression analysis. Here, we correct these issues and use best-practice approaches to snRNA-Seq differential expression, resulting 549 times fewer differentially expressed genes at a false discovery rate (FDR) of 0.05.