B cell and T cell receptor repertoires compose the adaptive immune receptor repertoire (AIRR) of an individual. The AIRR is a unique collection of antigen-specific receptors that drives adaptive immune responses, which in turn is imprinted in each individual AIRR. This supports the concept that the AIRR could determine disease outcomes, for example in autoimmunity, infectious disease and cancer. AIRR analysis could therefore assist the diagnosis, prognosis and treatment of human diseases towards personalized medicine. High-throughput sequencing, high-dimensional statistical analysis, computational structural biology and machine learning are currently employed to study the shaping and dynamics of the AIRR as a function of time and antigenic challenges. This Primer provides an overview of concepts and state-of-the-art methods that underlie experimental and computational AIRR analysis and illustrates the diversity of relevant applications. The Primer also addresses some of the outstanding challenges in AIRR analysis, such as sampling, sequencing depth, experimental variations and computational biases, while discussing prospects of future AIRR analysis applications for understanding and predicting adaptive immune responses.

B 细胞和 T 细胞受体库组成了个体的适应性免疫受体库 (AIRR)。 AIRR 是抗原特异性受体的独特集合，可驱动适应性免疫反应，而这种反应又印在每个单独的 AIRR 中。这支持了 AIRR 可以决定疾病结果的概念，例如自身免疫、传染病和癌症。因此，AIRR 分析可以帮助人类疾病的诊断、预后和治疗，实现个性化医疗。目前采用高通量测序、高维统计分析、计算结构生物学和机器学习来研究 AIRR 作为时间和抗原挑战的函数的形状和动态。本入门概述了实验和计算 AIRR 分析的概念和最先进的方法，并说明了相关应用的多样性。该入门指南还解决了 AIRR 分析中的一些突出挑战，例如采样、测序深度、实验变异和计算偏差，同时讨论了未来 AIRR 分析应用在理解和预测适应性免疫反应方面的前景。