Abstract
Advances in single-cell sequencing now allow simultaneous measurement of T cell and B cell antigen receptors together with rich molecular phenotypes. This review outlines the analytical challenges posed by these datasets, including complex clonotype structures, high sequence diversity, and the need to integrate receptor information with transcriptomic, epigenetic, and spatial readouts. The authors survey recent computational strategies for receptor reconstruction, clonotype definition, lineage and trajectory analysis, and antigen specificity inference, as well as emerging machine learning approaches. By synthesizing current methods and open problems, the review provides a roadmap for leveraging single-cell immune repertoire data to better understand adaptive immunity and its role in disease and therapy.