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

Methods
As described in the Materials and Methods section of https://www.biorxiv.org/content/10.1101/2024.11.26.625407v1