B cell receptor parent-child pairs for studying somatic hypermutation

Somatic hypermutation (SHM) is the diversity-generating process in
antibody affinity maturation. Probabilistic models of SHM are needed for
analyzing rare mutations, understanding the selective forces guiding
affinity maturation, and understanding the underlying biochemical process.
High throughput data offers the potential to develop and fit SHM models on
relevant data sets. Here we develop several out-of-frame and
synonymous-mutations datasets using the strategy of  Spisak, N.,
Walczak, A. M., & Mora, T. (2020). Learning the heterogeneous
hypermutation landscape of immunoglobulins from high-throughput repertoire
data. Nucleic Acids Research, 48(19), 10702–10712.
https://doi.org/10.1093/nar/gkaa825 for inferring parent-child pairs of
sequences.  We apply this to data from the following studies:
Briney, B., Inderbitzin, A., Joyce, C., & Burton, D. R. (2019).
Commonality despite exceptional diversity in the baseline human antibody
repertoire. Nature. https://doi.org/10.1038/s41586-019-0879-y Jaffe, D.
B., Shahi, P., Adams, B. A., Chrisman, A. M., Finnegan, P. M., Raman, N.,
Royall, A. E., Tsai, F., Vollbrecht, T., Reyes, D. S., Hepler, N. L.,
& McDonnell, W. J. (2022). Functional antibodies exhibit light
chain coherence. Nature, 611(7935), 352–357.
https://doi.org/10.1038/s41586-022-05371-z Tang, C., Krantsevich, A.,
& MacCarthy, T. (2022). Deep learning model of somatic
hypermutation reveals importance of sequence context beyond hotspot
targeting. iScience, 25(1), 103668.
https://doi.org/10.1016/j.isci.2021.103668 Vergani, S., Korsunsky, I.,
Mazzarello, A. N., Ferrer, G., Chiorazzi, N., & Bagnara, D.
(2017). Novel Method for High-Throughput Full-Length IGHV-D-J Sequencing
of the Immune Repertoire from Bulk B-Cells with Single-Cell Resolution.
Frontiers in Immunology, 8, 1157. https://doi.org/10.3389/fimmu.2017.01157