adsn

adsn analyzes single nuclei RNA sequencing (RNA-seq) data to characterize cell-type and subcluster-specific transcriptomic alterations associated with Alzheimer's disease.

Key Features:

• Single nuclei transcriptome mapping: Identifies nine distinct major clusters of cell-type specific and common gene expression patterns across control and Alzheimer's disease brains.
• Subcellular cluster characterization: Resolves functionally specialized subclusters including 5 microglial, 8 astrocyte, 6 neuronal, 6 oligodendrocyte, 4 oligodendrocyte progenitor cell (OPC), and 2 endothelial clusters with enrichments for specific ontological gene categories.
• Gene expression and APOE regulation: Detects cell- and subcluster-level expression changes, including repression of APOE in OPCs and astrocytes and enrichment of APOE in microglial AD subclusters.
• Integration with GWAS and regulatory modules: Integrates transcription factor regulatory modules with downstream genome-wide association study (GWAS) gene targets to identify subcluster-specific regulatory control, exemplified by TFEB's role in regulating astrocyte diversity and lysosomal function.

Scientific Applications:

• Cellular heterogeneity mapping: Provides a detailed map of cell-type and subcluster heterogeneity in human brains affected by Alzheimer's disease.
• Mechanistic insights into disease progression: Enables identification of cell-type specific contributions and regulatory patterns relevant to Alzheimer's disease progression.
• Linking genetics to cell states: Establishes functional links between specific cellular subpopulations and AD GWAS genes to elucidate coordinated control mechanisms underlying disease susceptibility.
• Identification of therapeutic targets: Identifies transcription factor networks and subcluster-specific regulators that may serve as candidate targets for therapeutic intervention.

Methodology:

Analysis of single nuclei RNA sequencing (RNA-seq) data to define nine major clusters and multiple subclusters, enrichment analysis of ontological gene categories for cluster-specific genes, and integration of transcription factor regulatory modules with downstream GWAS gene targets.