Antibodies are an integral part of the adaptive immune response, and are a critical component of both vaccine-induced and naturally-acquired immunity. The development of deep sequencing approaches in recent years has allowed us to sample a significant fraction of the diverse repertoire of B cell receptor sequences from which antibodies are made. These sequences encode a wealth of information on the somatic rearrangement and evolutionary processes that determine the contours of our antibody repertoires, and thus our ability to respond appropriately to pathogens and vaccines. Extracting this information, however, requires a careful inference approach across several different analysis steps. I will describe the computational approaches that we have taken to solving these problems, which constitute the partis software package, and describe their application in several projects, including HIV and Dengue data.
Duncan attended the University of California at Santa Cruz for his undergraduate studies in physics, completing his thesis on energy transport in condensed matter theory in 2005. He completed his PhD at the Massachusetts Institute of Technology in 2014, working on the Large Hadron Collider at the European particle physics laboratory (CERN). His thesis described the observation of Higgs boson decays to four leptons. Since 2014 he has worked in Frederick Matsen's lab at the Fred Hutchinson Cancer Research Center, first as a postdoctoral researcher and more recently as a staff scientist, writing new computational methods for the analysis of B cell receptor deep sequencing data.