Institute of Biomedical Engineering and Medical Informatics, School of Life Sciences, FHNW University of Applied Sciences and Arts Northwestern Switzerland, Muttenz, Switzerland.
Department of Pathology, Yale School of Medicine, New Haven, CT, USA.
Methods Mol Biol. 2022;2453:279-296. doi: 10.1007/978-1-0716-2115-8_16.
High-throughput sequencing of adaptive immune receptor repertoires (AIRR, i.e., IG and TR) has revolutionized the ability to carry out large-scale experiments to study the adaptive immune response. Since the method was first introduced in 2009, AIRR sequencing (AIRR-Seq) has been applied to survey the immune state of individuals, identify antigen-specific or immune-state-associated signatures of immune responses, study the development of the antibody immune response, and guide the development of vaccines and antibody therapies. Recent advancements in the technology include sequencing at the single-cell level and in parallel with gene expression, which allows the introduction of multi-omics approaches to understand in detail the adaptive immune response. Analyzing AIRR-seq data can prove challenging even with high-quality sequencing, in part due to the many steps involved and the need to parameterize each step. In this chapter, we outline key factors to consider when preprocessing raw AIRR-Seq data and annotating the genetic origins of the rearranged receptors. We also highlight a number of common difficulties with common AIRR-seq data processing and provide strategies to address them.
高通量测序适应性免疫受体库（AIRR，即 IG 和 TR）彻底改变了进行大规模实验以研究适应性免疫反应的能力。自 2009 年该方法首次被引入以来，AIRR 测序（AIRR-Seq）已被用于检测个体的免疫状态、识别抗原特异性或免疫状态相关的免疫反应特征、研究抗体免疫反应的发展，并指导疫苗和抗体疗法的开发。该技术的最新进展包括单细胞水平和与基因表达平行的测序，这使得可以采用多组学方法来详细了解适应性免疫反应。即使有高质量的测序，分析 AIRR-seq 数据也可能具有挑战性，部分原因是涉及的步骤众多，并且需要对每个步骤进行参数化。在本章中，我们概述了在预处理原始 AIRR-Seq 数据和注释重排受体的遗传起源时需要考虑的关键因素。我们还强调了常见的 AIRR-seq 数据处理常见困难，并提供了解决这些困难的策略。
