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scRepertoire 2: Enhanced and efficient toolkit for single-cell immune profiling.

Qile Yang1, Ksenia R Safina2,3, Kieu Diem Quynh Nguyen4

  • 1University of California Berkeley, Berkeley, California, United States of America.

Plos Computational Biology
|June 27, 2025
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Summary

scRepertoire 2 enhances single-cell immune receptor analysis with improved workflows and visualizations. This R package offers faster, more memory-efficient processing for single-cell immunogenomics research.

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Area of Science:

  • Immunology
  • Bioinformatics
  • Computational Biology

Background:

  • Single-cell adaptive immune receptor repertoire sequencing (scAIRR-seq) and single-cell RNA sequencing (scRNA-seq) are powerful tools for immune response profiling.
  • Analyzing large-scale single-cell immune data presents computational challenges.

Purpose of the Study:

  • To introduce scRepertoire 2, an updated R package for analyzing and visualizing single-cell immune receptor data.
  • To enhance the capabilities for clonotype tracking, repertoire diversity analysis, and comparative studies.
  • To improve computational performance for handling large single-cell datasets.

Main Methods:

  • Development and implementation of new algorithms within the scRepertoire R package.
  • Integration with existing single-cell analysis frameworks (Seurat, SingleCellExperiment).
  • Benchmarking of performance improvements in speed and memory usage compared to the previous version.

Main Results:

  • scRepertoire 2 offers enhanced workflows for clonotype tracking and repertoire diversity metrics.
  • Novel visualization modules are included for longitudinal and comparative analyses.
  • Significant performance gains: 85.1% increase in speed and 91.9% reduction in memory usage.

Conclusions:

  • scRepertoire 2 represents a significant advancement in single-cell immunogenomics analysis.
  • The updated package provides researchers with a more robust and efficient toolset.
  • Facilitates deeper insights into immune dynamics in various health and disease states.