  One of the key phenomena in the adaptive immune response to infection and
immunization is affinity maturation, during which antibody genes are mutated
and selected, typically resulting in a substantial increase in binding affinity
to the eliciting antigen. Advances in technology on several fronts have made it
possible to clone large numbers of heavy-chain light-chain pairs from
individual B cells and thereby identify whole sets of clonally related
antibodies. These collections could provide the information necessary to
reconstruct their own history--the sequence of changes introduced into the
lineage during the development of the clone--and to study affinity maturation
in detail. But the success of such a program depends entirely on accurately
inferring the founding ancestor and the other unobserved intermediates.
  I have developed an Empirical Bayes method that allows one to compute the
posterior distribution over ancestors, thereby giving a thorough accounting of
the uncertainty inherent in the reconstruction. I demonstrate the application
of this method on heavy-chain and light-chain clones, assess the reliability of
the inference, and discuss the sources of uncertainty.
