Enabling precision medicine with single cell omics and decentralized clinical studies

One of the most exciting consequences of the accessibility of single cell omics technologies is their use in new experimental designs. Beyond atlases, longitudinal studies with many timepoints are also yielding unprecedented volumes and formats of data. Driven by steadily decreasing sequencing costs and streamlined experimental workflows, single cell omics technologies, and especially single cell RNA sequencing technologies are now widely used from basic biological research to drug discovery and clinical studies. However, making use of data from these novel complex experimental design at massive scale requires scalable methods, such as the kallisto|bustools pre-processing workflow and the scvi-tools framework for probabilistic modeling of single cell omics. I will present on these and other tools which I helped develop during my PhD at Caltech, and show how such scalable methods are being leveraged in an ongoing longitudinal study on Inflammatory Bowel Disease (IBD) being executed by ImYoo, where participants have collectively mailed hundreds of capillary blood samples from across the United States. Instead of relying on a centralized hospital, these small samples of capillary blood are flexibly self-collected during flaring and quiescent states, yielding unique data that provides insights at critical biological and disease events. I will also briefly present ongoing research on innovative STEM education that I coordinate in an international partnership between the UC Berkeley School of Education and the Vilson Groh Institute with a large STEM education program for marginalized youth in Brazil (https://vilsongroh.org).