TACA

TACA aggregates over 1.1 million single-cell and single-nucleus transcriptomes from 26 brain datasets across hippocampus, cerebellum, and prefrontal cortex to enable cell type-specific molecular characterization and systems-level discovery of therapeutic targets in Alzheimer's disease.

Key Features:

• Data compendium: Integrates over 1.1 million single-cell and single-nucleus transcriptomes from 26 Alzheimer’s disease brain datasets.
• Tissue coverage: Includes major brain regions such as hippocampus, cerebellum, and prefrontal cortex.
• Cell types: Contains data for neurons, astrocytes, microglia, and oligodendrocytes.
• Differential expression analyses: Performs nearly 1,400 differential expression (DE) comparisons across multiple contrast types.
• Genotype- and sex-specific comparisons: Includes AD versus healthy control, sex-specific DE, and genotype-driven DE such as apolipoprotein E (APOE) ε4/ε4 versus APOE ε3/ε3 and TREM2 R47H versus common variants.
• Network and pathway analyses: Applies human protein-protein interactome network module analysis and pathway enrichment analysis following DE comparisons.
• Drug perturbation gene-set enrichment: Conducts gene-set enrichment analysis using over 700,000 drug perturbation profiles linking more than 10,000 human genes to approximately 13,000 drugs/compounds.
• Cell-cell interaction analyses: Performs over 400 cell-cell interaction analyses using 6,000 experimentally validated ligand-receptor interactions.

Scientific Applications:

• Cell type-specific molecular discovery: Identify cell type-specific transcriptomic alterations associated with Alzheimer’s disease.
• Genotype and sex effect characterization: Characterize genotype-driven (e.g., APOE ε4/ε4, TREM2 R47H) and sex-specific transcriptional changes in AD-relevant cell types.
• Therapeutic target and drug candidate prioritization: Prioritize targets and repurposing candidates by matching gene signatures to large-scale drug perturbation profiles.
• Systems-level pathway and network analysis: Map disease-associated protein-protein network modules and enriched biological pathways relevant to AD pathobiology.
• Intercellular communication mapping: Reveal disease-relevant cell-cell communication networks using validated ligand-receptor interaction data.

Methodology:

Compilation of >1.1 million single-cell and single-nucleus transcriptomes from 26 datasets; nearly 1,400 differential expression comparisons (AD vs healthy control; sex-specific; genotype-driven including APOE ε4/ε4 vs APOE ε3/ε3 and TREM2 R47H vs common variants); human protein-protein interactome network module analysis; pathway enrichment analysis; gene-set enrichment analysis including against >700,000 drug perturbation profiles linking >10,000 genes to ~13,000 drugs/compounds; and >400 cell-cell interaction analyses using 6,000 experimentally validated ligand-receptor interactions.