Our lab is building powerful computational methods to elucidate the interaction between rare variants and common SNPs by integrating whole-exome data and SNP array data in order to determine the complex genetic underpinnings of common diseases.
In collaboration with Seoul National University Hospital, our lab is analyzing ~5,000 undiagnosed rare disease patients to identify novel disease causal genes using whole-genome sequencing as well as single-cell whole genome sequencing.
Although immunotherapy has become a widely used standard treatment for cancer, only a minority of patients respond to it. Our lab is creating a computational predictive model to reveal new biomarkers for immunotherapy response and understand the resistance mechanism in collaboration with Yale Cancer Center.
Recent advances in spatial transcriptomic technology have made it possible to dissect cellular heterogeneity while keeping spatial information. However, precise mapping of different neighboring cell types is still challenging due to insufficient resolution. Our lab is developing computational methods of cell-type deconvolution by integrating single-cell RNA-seq data and spatial transcriptomics data in collaboration with geninus.
