The reconstruction of clonal families (CFs) in B-cell receptor (BCR) repertoire analysis is a crucial step to understand the adaptive immune system and how it responds to antigens. The BCR repertoire of an individual is formed throughout life and is diverse due to several factors such as gene recombination and somatic hypermutation. The use of Adaptive Immune Receptor Repertoire sequencing (AIRR-seq) using next generation sequencing enabled the generation of full BCR repertoires that also include rare CFs. The reconstruction of CFs from AIRR-seq data is challenging and several approaches have been developed to solve this problem. Currently, most methods use the heavy chain (HC) only, as it is more variable than the light chain (LC). CF reconstruction options include the definition of appropriate sequence similarity measures, the use of shared mutations among sequences, and the possibility of reconstruction without preliminary clustering based on V- and J-gene annotation. In this study, we aimed to systematically evaluate different approaches for CF reconstruction and to determine their impact on various outcome measures such as the number of CFs derived, the size of the CFs, and the accuracy of the reconstruction. The methods were compared to each other and to a method that groups sequences based on identical junction sequences and another method that only determines subclones. We found that after accounting for data set variability, in particular sequencing depth and mutation load, the reconstruction approach has an impact on part of the outcome measures, including the number of CFs. Simulations indicate that unique junctions and subclones should not be used as substitutes for CF and that more complex methods do not outperform simpler methods. Also, we conclude that different approaches differ in their ability to correctly reconstruct CFs when not considering the LC and to identify shared CFs. The results showed the effect of different approaches on the reconstruction of CFs and highlighted the importance of choosing an appropriate method.

中文翻译：

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B 细胞克隆家族推断方法的系统评估

B 细胞受体 (BCR) 库分析中克隆家族 (CF) 的重建是了解适应性免疫系统及其如何响应抗原的关键步骤。个体的 BCR 库是在一生中形成的，并且由于基因重组和体细胞超突变等多种因素而多种多样。使用下一代测序的适应性免疫受体库测序 (AIRR-seq) 能够生成完整的 BCR 库，其中还包括稀有的 CF。从 AIRR-seq 数据重建 CF 具有挑战性，并且已经开发了几种方法来解决这个问题。目前，大多数方法仅使用重链 (HC)，因为它比轻链 (LC) 更具可变性。 CF 重建选项包括适当序列相似性度量的定义、序列之间共享突变的使用以及无需基于 V 和 J 基因注释进行初步聚类即可重建的可能性。在本研究中，我们的目的是系统地评估 CF 重建的不同方法，并确定它们对各种结果指标的影响，例如导出的 CF 数量、CF 大小和重建的准确性。将这些方法相互比较，并与基于相同连接序列对序列进行分组的方法和仅确定亚克隆的另一种方法进行比较。我们发现，在考虑了数据集变异性之后，特别是测序深度和突变负载，重建方法对部分结果测量产生影响，包括 CF 的数量。模拟表明，独特的连接和亚克隆不应用作 CF 的替代品，并且更复杂的方法并不优于更简单的方法。此外，我们得出的结论是，不同的方法在不考虑 LC 的情况下正确重建 CF 的能力以及识别共享 CF 的能力有所不同。结果显示了不同方法对 CF 重建的影响，并强调了选择合适方法的重要性。