This semester’s project focused on developing a complete single-cell RNA-sequencing pipeline and using it to map how Alzheimer’s disease alters gene-expression patterns across brain cell types.

Students built the workflow from the ground up—preprocessing raw data, filtering cells and genes, normalizing counts, identifying highly variable genes, running PCA, clustering, and visualizing results with UMAP—to uncover meaningful shifts between healthy and Alzheimer’s-affected cells.

By applying marker-gene analysis and statistical tests, the project aimed to generate clear biological insights into how amyloid-β–related pathology is reflected in single-cell transcriptional changes.