Yang Qile, Safina Ksenia R, Nguyen Kieu Diem Quynh, Tuong Zewen Kelvin, Borcherding Nicholas
University of California Berkeley, Berkeley, California, United States of America.
Division of Hematology, Brigham and Women's Hospital, Boston, Massachusetts, United States of America.
PLoS Comput Biol. 2025 Jun 27;21(6):e1012760. doi: 10.1371/journal.pcbi.1012760. eCollection 2025 Jun.
Single-cell adaptive immune receptor repertoire sequencing (scAIRR-seq) and single-cell RNA sequencing (scRNA-seq) provide a transformative approach to profiling immune responses at unprecedented resolution across diverse pathophysiologic contexts. This work presents scRepertoire 2, a substantial update to our R package for analyzing and visualizing single-cell immune receptor data. This new version introduces an array of features designed to enhance both the depth and breadth of immune receptor analysis, including improved workflows for clonotype tracking, repertoire diversity metrics, and novel visualization modules that facilitate longitudinal and comparative studies. Additionally, scRepertoire 2 offers seamless integration with contemporary single-cell analysis frameworks like Seurat and SingleCellExperiment, allowing users to conduct end-to-end single-cell immune profiling with transcriptomic data. Performance optimizations in scRepertoire 2 resulted in a 85.1% increase in speed and a 91.9% reduction in memory usage from the first version over the range repertoire size tested in benchmarking, addressing the demands of the ever-increasing size and scale of single-cell studies. This release marks an advancement in single cell immunogenomics, equipping researchers with a robust toolset to uncover immune dynamics in health and disease.
单细胞适应性免疫受体组库测序(scAIRR-seq)和单细胞RNA测序(scRNA-seq)提供了一种变革性方法,能够以前所未有的分辨率在不同病理生理背景下描绘免疫反应。本文介绍了scRepertoire 2,这是我们用于分析和可视化单细胞免疫受体数据的R包的重大更新。这个新版本引入了一系列旨在增强免疫受体分析深度和广度的功能,包括改进的克隆型追踪工作流程、组库多样性指标,以及有助于纵向和比较研究的新型可视化模块。此外,scRepertoire 2与Seurat和SingleCellExperiment等当代单细胞分析框架实现了无缝集成,允许用户利用转录组数据进行端到端的单细胞免疫分析。在基准测试中,scRepertoire 2的性能优化使速度提高了85.1%,内存使用量比第一个版本减少了91.9%,满足了单细胞研究规模不断扩大的需求。此版本标志着单细胞免疫基因组学的进步,为研究人员提供了一个强大的工具集,以揭示健康和疾病中的免疫动态。