Liting Zhang, a PhD candidate in the Computer Science Department, under the guidance of Dr. Xian Mallory, has recently made a significant contribution to the field of computational biology by publishing their work in the esteemed interdisciplinary journal, Genome Research, the impact factor of which is 9.438. The research paper, titled “Integrating SNVs and CNAs on a Phylogenetic Tree from Single-Cell DNA Sequencing Data,” represents a collaborative effort, featuring co-authors Dr. Hank Bass, a professor from the Biology Department, and Dr. Jerome Irianto, an assistant professor from the College of Medicine.

Their collective effort led to the development of an innovative computational tool known as SCsnvcna. This is the first computational tool that reconstructs the phylogenetic tree where the cancer cells in a cancer patient evolve on, whereas the tree has two types of mutations, the small one called single nucleotide variations and the large one called copy number alterations. Currently due to the limitation of the sequencing technology, the two types of mutations are detected from two sets of cells instead of one, which raised computationally challenges to reconcile both SNVs and CNAs on one phylogenetic tree. However, it is essential for the medical providers and cancer researchers to have one tree where both SNVs and CNAs are placed. Zhang et al. used multiple computational techniques such as probabilistic graphic model, Monte Carlo Markov Chain (MCMC) sampling, as well as various statistical analysis that enabled them to successfully reconcile SNVs and CNAs on one tree. Zhang et al. did comprehensive simulation studies that showed the efficacy and robustness of SCsnvcna. In addition, a test on two existing colorectal cancer samples showed that SCsnvcna can not only accurately infer the tree with both SNVs and CNAs, but can also correct the errors that the existing state-of-the-art computational tools made, and thus help to further understand how colorectal cancer cells grow by gaining mutations such as SNVs and CNAs.