We analyzed the data from each class and region (109 analyses total) using semi-supervised ICA, in which we excluded 1,157 ICs as technical and classified the remaining 601 ICs as “biological ICs” (STAR Methods). We then grouped cells based on combinations of “biological IC” cell loadings into 565 subclusters using network-based clustering (Shekhar et al., 2016; Waltman and van Eck, 2013) (Figure 1E and Figures S2J,K). Of these subclusters, 323 were neuronal, derived from 368 biological ICs (Data S3). Across subclusters, patterns of similar RNA expression generally corresponded to cell class rather than brain region (Figure S1F,G).
