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

Abstract

Mathys et al., conducted the first single-nucleus RNA-Seq study (snRNA-Seq) of Alzheimers 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 time2. 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.