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/s4158..., As described in the Materials and Methods section of https://www.biorxiv.org/content/10.1101/2024.11.26.625407v1, , # B cell receptor parent-child pairs for studying somatic hypermutation

[https://doi.org/10.5061/dryad.np5hqc044](https://doi.org/10.5061/dryad.np5hqc044)

## Description of the data and file structure

This is reprocessed B-cell receptor (BCR) sequence data as described in [https://www.biorxiv.org/content/10.1101/2024.11.26.625407v1](https://www.biorxiv.org/content/10.1101/2024.11.26.625407v1) 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* **566**, 393–397. [https://doi.org/10.1038/s41586-019-0879-y](https://doi.org/10.1038/s41586-019-0879-y)

Jaffe, D.B., Shahi, P., Adams, B.A. *et al.* (2022). Functional antibodies exhibit light chain coherence. *Nature* **611**, 352–357. [https://doi.org/10.1038/s41586-022-05371-z](https://doi.org/10.1038/s41586-022-05371-z)

Spisak, N., Walczak, A. M., & Mora, T. (2020). Learning the heterogeneous hype...

体细胞超突变（Somatic hypermutation, SHM）是抗体亲和力成熟过程中产生序列多样性的核心机制。为分析稀有突变事件、解析驱动亲和力成熟的选择压力，以及阐明其背后的生化过程，需构建SHM的概率模型。高通量免疫组库数据为在相关数据集上开发并拟合SHM模型提供了可行途径。本研究遵循Spisak等人（2020）的研究策略，构建了多套读码框外突变与同义突变数据集，用于推断抗体序列的亲子对关系。该原始参考文献为：Spisak, N., Walczak, A. M., & Mora, T. (2020). 从高通量免疫组库数据学习免疫球蛋白的异质性超突变景观. 《核酸研究》, 48(19), 10702–10712. https://doi.org/10.1093/nar/gkaa825

本研究将该方法应用于以下研究的数据：
Briney, B., Inderbitzin, A., Joyce, C., & Burton, D. R. (2019). 基础人类抗体库虽具极高多样性但仍存在共性. *Nature*. https://doi.org/10.1038/s4158..., 详细实验方法详见预印本https://www.biorxiv.org/content/10.1101/2024.11.26.625407v1的材料与方法部分。
# 用于体细胞超突变研究的B细胞受体（B-cell receptor, BCR）亲子对数据集 [https://doi.org/10.5061/dryad.np5hqc044]

## 数据与文件结构说明
本数据集为经重新处理的B细胞受体（B-cell receptor, BCR）序列数据，相关细节详见预印本[https://www.biorxiv.org/content/10.1101/2024.11.26.625407v1]，数据来源于以下研究：
1. Briney, B., Inderbitzin, A., Joyce, C., & Burton, D. R. (2019). 基础人类抗体库虽具极高多样性但仍存在共性. *Nature* **566**, 393–397. [https://doi.org/10.1038/s41586-019-0879-y]
2. Jaffe, D.B., Shahi, P., Adams, B.A. 等. (2022). 功能性抗体展现轻链一致性. *Nature* **611**, 352–357. [https://doi.org/10.1038/s41586-022-05371-z]
3. Spisak, N., Walczak, A. M., & Mora, T. (2020). 从高通量免疫组库数据学习免疫球蛋白的异质性超突变景观……