Home Department: undeclared
Mentor: Wing Wong, Statistics and Biomedical Data Science

Current bulk gene analysis methods cannot distinguish between subpopulations of cells in a heterogeneous sample, making it impossible to identify differences in the transcriptional profiles of varying cell types, and to the changing composition of cell subpopulations within a sample. The rise of single-cell genomics data allows scientists to differentiate gene expression levels of individual cell types within a heterogeneous sample. Miranda will use a matrix factorization method developed in the Wong Lab to couple different kinds of single-cell sequencing data in order to discover novel genetic regulators of disease and phenotypic variation between cell types. This work has exciting potential applications to all fields of medicine.