DAM-DRUG: Pre-computed datasets for integrative single-cell analysis of Alzheimer's disease microglia (Özkurt, 2026)

File Name Description microglia_trajectory.h5ad Processed AnnData: 236,002 microglial nuclei (84 SEA-AD donors) with scVI correction, substate annotations, PAGA trajectory, and pseudotime. (Fig. 1, Supp. Fig. S3) counts_raw.h5 Raw count matrix (HDF5) for 15 MTG cell types used in CellChat ligand-receptor analysis. (Supp. Fig. S8) adj_matrix_aggregated.tsv Consensus GRN adjacency matrix aggregated across 5 GRNBoost2 seeds (1.46 M TF–target edges). regulons_aggregated.csv 46 pySCENIC regulons passing consensus and RcisTarget filters (includes AUC, NES, and motif annotation). vina_scores_IKZF1_8RQC_CRBN.csv AutoDock Vina scores for 1,677 CNS compounds docked to IKZF1 (PDB: 8RQC). vina_scores_IRF8_AF2_DBD_prep.csv AutoDock Vina scores for 1,677 CNS compounds docked to IRF8 (AlphaFold2 DBD). vina_scores_PPARG_1FM9_LBD_prep.csv AutoDock Vina scores for 1,677 CNS compounds docked to PPARG (PDB: 1FM9). vina_scores_RUNX1_1LJM_Runt_prep.csv AutoDock Vina scores for 1,677 CNS compounds docked to RUNX1 (PDB: 1LJM). vina_scores_MAF_4EOT_bZIP_prep.csv AutoDock Vina scores for 1,677 CNS compounds docked to MAF (PDB: 4EOT). vina_scores_BHLHE41_AF2_bHLH_prep.csv AutoDock Vina scores for 1,677 CNS compounds docked to BHLHE41 (AlphaFold2 bHLH). gnina_scores_IKZF1_8RQC_CRBN.csv GNINA CNN rescoring of top Vina poses for IKZF1. gnina_scores_IRF8_AF2_DBD_prep.csv GNINA CNN rescoring of top Vina poses for IRF8. gnina_scores_PPARG_1FM9_LBD_prep.csv GNINA CNN rescoring of top Vina poses for PPARG. gnina_scores_RUNX1_1LJM_Runt_prep.csv GNINA CNN rescoring of top Vina poses for RUNX1. gnina_scores_MAF_4EOT_bZIP_prep.csv GNINA CNN rescoring of top Vina poses for MAF. gnina_scores_BHLHE41_AF2_bHLH_prep.csv GNINA CNN rescoring of top Vina poses for BHLHE41. consensus_hits.csv Compounds passing both Vina ≤ −8.5 kcal/mol and GNINA CNN score ≥ 0.75 across all targets. mmpbsa_summary.csv MM-GBSA binding free energies (ΔG) for Tier-1 and Tier-2 hits from 1 ns GROMACS MD trajectories. selectivity_table.csv Selectivity index (SI) for 6 validated hits against DRD2, HTR2A, and hERG off-targets. deseq2_all_genes.csv Full pyDESeq2 results for GSE95587 (fusiform gyrus, AD vs control, n=117). deseq2_target_tfs.csv pyDESeq2 results subset to 10 target TFs (IKZF1, IRF8, SPI1, PPARG, RUNX1, CEBPB, MAF, RELB, BHLHE40, BHLHE41). dge_pb_DAM_vs_Homeostatic.csv Full pyDESeq2 pseudobulk results for DAM vs Homeostatic microglia (84 SEA-AD donors; 6,712 significant genes). (Fig. 2, Supp. Fig. S1) dge_pb_IRM_vs_Homeostatic.csv Full pyDESeq2 pseudobulk results for IRM vs Homeostatic microglia (84 SEA-AD donors; 3,956 significant genes). (Fig. 2, Supp. Fig. S1) dge_pb_LAM_vs_Homeostatic.csv Full pyDESeq2 pseudobulk results for LAM vs Homeostatic microglia (84 SEA-AD donors; 2,985 significant genes). (Fig. 2, Supp. Fig. S1)