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Spring 2026 - Mining Gene Expression in Human Cells Using Single-Cell Data
Project Description
This semester’s project focuses on mining gene expression in human cells using single-cell RNA transcript data from Tabula Sapiens, with the goal of understanding oxidative stress and antioxidant defenses as a readout of cellular redox state.
Students will work with large-scale single-cell datasets (H5AD files analyzed in Python) and connect core biological concepts, ROS production, antioxidant neutralization, and redox homeostasis, to measurable shifts in transcriptional programs.
By quantifying expression in oxidative-stress and antioxidant pathways, teams aim to build interpretable “oxidative health”/redox metrics and use them to compare patterns across cell types and patient groups, asking how redox capacity varies by biology (cell identity) and by context (disease, chronic conditions, age).
Fall 2025 - scRNAseq for Alzheimer's
Project Description
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.
