Single-cell transcriptomic reveals heterogeneity within monocyte and macrophage populations with disease-specific difference. (A) Monocyte/macrophage (n = 8,318) subclustering reveals 10 subclusters (left), also colored by patient ID (middle) and disease condition (right). (B) Heatmap of subtype top 10 DE genes in each of the monocyte/macrophage subcluster. (C) Expression of marker genes in monocyte/macrophage subclusters by disease conditions. (D) Two-sided Fisher’s exact test on abundance of detailed macrophage (left) and monocyte (right) subclusters between TB conditions. Holm’s method was applied to adjust P values for multiple-testing correction. Statistical annotations: P value < 0.05 (*), P value < 0.01 (**), P value < 0.001 (***), fold-change >1 (Δ), fold-change >2 (ΔΔ), and fold-change <1 (∇). (E) Cell2loc imputed macrophage (left) and monocyte (right) abundance distribution on the Visium dataset grouped by TB and granuloma status (Materials and methods). The 5% quantile of the estimated posterior distribution of cell abundance at each Visium spot is displayed, representing the value of cell abundance that the model has high confidence in. Two-sided Mann–Whitney U test without correction were used for statistical testing. Statistical annotations: P value < 0.0001 (****). (F) Similar to E, but grouped by TB status and HIV status.