Scholarlink

Background <p>The immune repertoire (IR) reflects the adaptive immune system of an organism by encompassing the diversity and composition of receptor sequences expressed by T and/or B lymphocytes. Despite significant advances in the efficiency and accuracy of antigen discrimination facilitated by high-throughput sequencing technologies, IR analysis remains challenging due to its extraordinary heterogeneity and the high dimensional nature of sequencing data.</p> Main body <p>This review provides an overview of the key steps involved in IR profiling, highlighting factors that impact data accuracy, including sample sources, sequencing data quality control, repertoire characterization derived from the vast diversity of millions of receptors, and the specificity in lymphocyte-peptide interactions. Several bioinformatics pipelines have emerged to facilitate IR analysis, offering various computational tools to process and interpret complex datasets. Furthermore, we explore the integration of machine learning and multi-omics approaches, which are driving deeper insights into IR analysis.</p> Conclusions <p>By examining different perspectives, we summarize recent methodological and computational advancements in the field and provide unique insights into the evolving landscape of IR data analysis.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Decoding adaptive immunity: advanced strategies in T and B cell repertoire analysis

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年2月13日

查看全文
  • Xinjie Yu,
  • Nan Peng,
  • Wenjing Pan,
  • Shenbo Xie,
  • Congli Tang,
  • Xue Wang,
  • Hongna Liu,
  • Yifei Shi,
  • Yuqi He,
  • Wanqing Wu,
  • Daniel Weber,
  • Libo Nie,
  • Yuan Liu,
  • Zhu Chen,
  • Yan Deng,
  • Miranda Byrne-Steele,
  • Zhe Wang,
  • Song Li

摘要

Background

The immune repertoire (IR) reflects the adaptive immune system of an organism by encompassing the diversity and composition of receptor sequences expressed by T and/or B lymphocytes. Despite significant advances in the efficiency and accuracy of antigen discrimination facilitated by high-throughput sequencing technologies, IR analysis remains challenging due to its extraordinary heterogeneity and the high dimensional nature of sequencing data.

Main body

This review provides an overview of the key steps involved in IR profiling, highlighting factors that impact data accuracy, including sample sources, sequencing data quality control, repertoire characterization derived from the vast diversity of millions of receptors, and the specificity in lymphocyte-peptide interactions. Several bioinformatics pipelines have emerged to facilitate IR analysis, offering various computational tools to process and interpret complex datasets. Furthermore, we explore the integration of machine learning and multi-omics approaches, which are driving deeper insights into IR analysis.

Conclusions

By examining different perspectives, we summarize recent methodological and computational advancements in the field and provide unique insights into the evolving landscape of IR data analysis.