Dr. Wei is focusing on inflammatory breast cancer (IBC), an aggressive disease subtype without known genetic signatures. This suggests that IBC could be highly heterogeneous (the cells within a tumor are genetically diverse), and the tumor microenvironment (the environment surrounding a tumor) may be important for disease progression and therapeutic resistance. He is developing a computational toolkit to characterize the IBC tumor spatial heterogeneity and tumor microenvironment. He will leverage cutting-edge deep learning approaches to associate histopathology findings from tumor samples with single cell spatial sequencing information. This project will provide a better understanding of IBC initiation, progression and therapy responses at a molecular level.
Dr. Wei will use open-access single cell and spatial sequencing data analysis tools, e.g. Seurat and Scanpy to analyze data. He will also use specific computational tools for different analytical purposes, e.g. RNA Velocity and Monocle to infer cell differentiation, CytoTRACE, SCENT to infer cell differentiation potentials, and SCENIC to infer the transcriptional factors and gene regulatory network. Besides, he will develop novel algorithms/computational tools for spatial and single-cell sequencing data analysis.
