Analyzing Human PFC snRNA-seq Data

The snRNA-seq datasets (raw or gene expression matrices) of the human PFC used in this study were downloaded from the NCBI Gene Expression Omnibus database (GEO)¹ under accession numbers GSE157827 (Lau et al., 2020 (link)), GSE174367 (Morabito et al., 2021 (link)), containing 24 AD and 17 control samples in total. After merging all the datasets, cells with less than 200 unique molecular identifiers (UMIs), more than 5,000 UMIs, or mitochondrial counts greater than 20% were filtered out. Genes expressed in fewer than three cells were also filtered out. Seurat (version 4.0)² was used for a wide variety of single-cell analyses, including normalization, scaling, batch correction, dimensionality reduction, clustering, and visualization. We used the harmony package³ for the batch correction. The expression of known marker genes in the CNS was used as a reference for the annotation of different cell types. All statistical analyses were conducted using the R software (version 4.0.2).