clonevdjseq:一个工作流和生物信息管理系统,用于对来自克隆库的VDJ序列进行测序,存档和分析
Keith Mitchell1,2, Samuel Hunter3, Lutz Froenicke4
1Department of Physiology and Membrane Biology, University of California Davis School of Medicine, Davis, CA, USA. kgmitchell@ucdavis.edu.
BMC bioinformatics
|July 22, 2025
概括
clonevdjseq是一个新的生物信息学工具,用于分析来自大型数据集的B细胞和T细胞受体序列. 它为研究抗原识别和抗体开发的研究人员提供了灵活和可扩展的解决方案.
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:
- 下一代测序产生了大量的B细胞受体 (BCR) 和T细胞受体 (TCR) 序列数据.
- 现有的生物信息学工具在大型克隆数据集所需的规模和灵活性方面扎.
- 之前的混合体依赖代码缺乏广泛的系统兼容性.
研究的目的:
- 为BCR/TCR序列分析开发一个集成,可访问和可扩展的软件解决方案.
- 为了提高大型克隆数据集的灵活性和建模能力.
- 为更广泛的系统兼容性提供技术补充.
主要方法:
- 使用 Nextflow 和 Django 开发了 clonevdjseq.
- 集成模块用于读取处理,放大器消噪和质量控制.
- 基于高吞吐量库准备协议构建的.
- 包括可选的数据库和用于数据传播的网络应用程序.
主要成果:
- clonevdjseq有效地处理大型杂交细胞库和同质细胞群.
- 管道模块可以处理配对的可变轻/重链 (BCR) 和α/β,delta/gamma链 (TCR).
- 处理的数据经过数千个单克隆抗体的验证,使得重组抗体的开发成为可能.
- 生成的序列为NeuroMabSeq倡议和其他建模应用做出了贡献.
结论:
- clonevdjseq为VDJ数据集处理和分析提供了一个全面的,可扩展的解决方案.
- 模块化设计,动态管道和数据库集成确保了高效的数据管理.
- 公开可用的平台支持对混合体和单细胞群的BCR/TCR序列存档和传播.
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