First, we used standard pipelines to uniformly process single-cell RNA-seq data from PsychENCODE, in conjunction with other single-cell studies on the brain (14, 16, 20). Then we assembled profiles of brain cell types, including both excitatory and inhibitory neurons (denoted as Ex1 to Ex9 and In1 to In8, respectively, according to previous conventions), major nonneuronal types (e.g., microglia and astrocytes), and additional cell types associated with development (21). Depending on the underlying sequencing and quantification, our profiles were of two fundamentally different formats, transcripts per kilobase million (TPM) and unique molecular identifier (UMI) counts. The former (TPM profiles) includes the uniformly processed PsychENCODE developmental single-cell data merged with published adult and developmental data (fig. S4 and table S2) (14, 16). By contrast, the UMI profiles are built by merging PsychENCODE adult single-cell profiles with other recently published data-sets (14). Both formats share common neuronal and major nonneuronal cell types and are used interchangeably in various analyses in this study (fig. S5 and tables S3 and S4). Moreover, the expression values of biomarker genes for the same cell type were correlated
