Many blood cancers, including leukemia and multiple myeloma, arise when early blood-forming cells do not develop properly. These aberrant cell fate choices cause abnormal blood cells to grow and divide uncontrollably. By combining lineage tracing, single-cell RNA sequencing (scSeq), and computational analysis, Dr. Wang aims to first develop a theoretical foundation and then build computational pipelines that reliably infer the order of events in cellular differentiation from these datasets. The results of this research may empower other biologists to systematically map out cell fate choice in their preferred systems. Applying the tools developed here to study perturbed blood formation (hematopoiesis) may also accelerate progress in understanding blood cancers.

Dr. Wang developed a novel method, CoSpar, that can directly integrate single-cell RNAseq data and clonal measurements to infer a transition map, which allows interesting predictions like early fate bias. The method makes reasonable assumptions to improve the prediction: cells have limited differentiation potential and neighboring cells tend to share similar fate outcomes. He is applying this method to published lineage tracing datasets in hematopoiesis, reprogramming, and direct lung differentiation.