From perturbation screens to therapeutic gene editing: Statistical methods for CRISPR applications
CRISPR genome editing is radically transforming biology and medicine. Biologically, CRISPR enables targeted perturbations of genes, revealing regulatory mechanisms and networks underlying diseases. Medically, CRISPR can permanently “fix” mutations in patient DNA, providing a one-time, curative treatment for genetic disorders. CRISPR perturbation experiments and therapeutic development efforts have produced reams of high-throughput, noisy data. In this talk I show how innovative statistical methods can help unlock the potential of CRISPR technology for biological discovery and curative genetic medicine. I highlight several recent and ongoing projects at the intersection of perturbation screening, therapeutic gene editing, robust statistics, and causal inference.
Timothy Barry is a postdoctoral fellow at Boston Children’s Hospital working with Daniel Bauer. He completed his PhD in Statistics at Carnegie Mellon University under the supervision of Kathryn Roeder and Eugene Katsevich. He works at the interface of statistics, computer science, and genomics, with a focus on statistical problems arising in the context of perturbation screen experiments and therapeutic gene editing. He is supported by a Young Investigator Award sponsored through the Uplifting Athletes foundation and Shwachman-Diamond Syndrome Alliance.
Hybrid, but in-person attendance is encouraged.