Discovering Tissue Microenvironments Through Spatial Transcriptomics Analysis
Peng He, Professor
UC San Francisco
Applications for Fall 2025 are closed for this project.
This project investigates how cells behave and interact in their native environments by analyzing spatial gene expression data. Interns will use Visium and Xenium spatial transcriptomics datasets to identify tissue microenvironments, reconstruct 3D spatial maps, and apply computational tools like NicheFormer.
Role: Subprojects:
Analyze spatial transcriptomics data from human tissues
Align adjacent slices to construct 3D spatial maps
Develop and apply feature extraction pipelines from H&E images
Run spatial niche analysis tools and integrate lineage tracing data
Qualifications: Programming experience in R or Python; interest in spatial genomics and data visualization
Day-to-day supervisor for this project: Konstantinos Stasinos, Staff Researcher
Hours: to be negotiated
Off-Campus Research Site: on site/hybrid/off-campus all acceptable
Related website: https://profiles.ucsf.edu/peng.he
Related website: https://peng-he-lab.github.io/