Two preprints on inferring affinity-fitness response in germinal centers from trees

Two collaborative preprints investigate how fitness of affinity-maturing B cells depends on affinity changes in their mutating B-cell receptors, both using B-cell lineage trees from our recent GC (germinal center) replay preprint

• Preprint led by Thanasi Bakis models trees via phylogenetic birth-death processes and performs Bayesian posterior inference of affinity-fitness response.

• Preprint by Duncan Ralph uses the same trees but takes a simulation-based deep-learning approach to inferring parameters.

In the GC Replay paper we inferred an affinity-fitness landscape by modeling the time evolution of distributions of affinities (representing B-cells during GC evolution). Thanasi’s and Duncan’s papers both take a more fine-grained approach to this inference problem, leveraging the details of GC lineage trees with affinities assigned to nodes, rather than coarse-graining to affinity distributions.