We analyse single-cell sequencing data to investigate tumour evolution from individual cells.
Cutting-edge single-cell sequencing technologies provide a view of tumour evolution at unprecedented resolution. These technologies enable us to explore the cancer genomes of individual cells, but they generally provide only a very limited amount of sequencing reads per cell. Thus, the potential of using such technologies for investigating the cancer evolutionary process is limited by the extreme sparsity of the resulting sequencing data.
Our lab focuses on the design and development of computational methods and algorithms to investigate tumour evolution and intra-tumour heterogeneity from single-cell sequencing data. Such computational methods leverage the features of single-cell sequencing technologies and integrate multiple sources of information to overcome the weaknesses and missing information or errors of these technologies. When appliying such methods on single-cell sequencing data, we unveil key mechanisms of tumour evolution and insights into the cancer evolutionary processes.