Single-cell RNA-seq (scRNA-seq) is widely used to investigate the composition of complex tissues since the technology allows researchers to define cell-types using unsupervised clustering of the transcriptome. However, due to differences in experimental methods and computational analyses, it is often challenging to directly compare the cells identified in two different experiments. scmap is a method for projecting cells from a scRNA-seq experiment on to the cell-types or individual cells identified in a different experiment.
The Hemberg group is interested in developing quantitative models of gene expression. Our approach is theoretical and we strive to develop novel mathematical models as well as computational tools that can be used by other researchers.
We explore the consequences of genome variation on human cell biology, and thus gene function in health and disease. We conduct large-scale systematic screens to discover the impact of naturally-occurring and engineered genome mutations in human iPS cells, their differentiated derivatives, and other cell types.