从重链和轻链BCR序列与Dowser配对中推断出B细胞类型
Cole G Jensen1, Jacob A Sumner1,2, Steven H Kleinstein1,3,4
1Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06511, USA.
bioRxiv : the preprint server for biology
|October 24, 2023
概括
将配对抗体光链纳入遗传树结构可以显著提高准确性和可重复性. 建议采用具有分离基因分区的最大概率方法来进行强大的B细胞分化,特别是在混合数据类型的情况下.
科学领域:
- 免疫学 免疫学 免疫学
- 生物信息学是一种生物信息学.
- 计算生物学 计算生物学
背景情况:
- 对于免疫反应至关重要的抗体,是由可变的重和轻链构成的,最初是B细胞受体 (BCR).
- BCR的多样性源于体质突变和选择,产生具有独特突变历史的独特B细胞克隆.
- 重建这些突变历史依赖于家族遗传树,但对配对重链和轻链序列的最佳方法仍然不清楚.
研究的目的:
- 从单细胞测序中研究使用对重和轻链序列构建B细胞类基因的最佳策略.
- 评估将光链数据纳入研究对遗传树推断的准确性和可重复性的影响.
主要方法:
- 利用单细胞测序的重链和轻链配对测序来构建家族遗传树.
- 对比了各种遗传学推断方法,评估了包括轻链数据的影响.
- 研究方法,以解决当轻链数据不完整时的分支长度偏差,特别是混合测序数据集.
主要成果:
- 整合光链大大提高了被测试方法的基因树准确性和可重复性.
- 包括轻链的好处超过了树木建设方法之间的差异.
- 对于重链分区和轻链分区,具有分离分支长度的最大概率方法有效地消除了混合数据集中的分支长度偏差.
结论:
- 使用分离分支长度用于重链和轻链基因分区的最大概率方法有效地消除了分支长度偏差.
- 建议使用最大概率与独立分区用于强大的B细胞原型学,特别是在结合不同的数据类型时.
- 在R包Dowser中开发和实施这些推方法,以实现更广泛的可访问性.
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