A toolkit for single-cell immune receptor profiling • scRepertoire

Introduction

Single-cell sequencing is an emerging technology in the field of immunology and oncology that allows researchers to couple RNA quantification and other modalities, like immune cell receptor profiling at the level of an individual cell. A number of workflows and software packages have been created to process and analyze single-cell transcriptomic data. These packages allow users to take the vast dimensionality of the data generated in single-cell-based experiments and distill the data into novel insights. Unlike the transcriptomic field, there is a lack of options for software that allow for single-cell immune receptor profiling. Enabling users to easily combine RNA and immune profiling, the scRepertoire framework supports use of 10x, AIRR, BD, MiXCR, TRUST4, and WAT3R single-cell clonal formats and interaction with popular R-based single-cell data pipelines.

Applying Deep Learning to VDJ data

scRepertoire is compatible and integrated with the R packages Trex for convolutional-neural-network-based autoencoding of the T cell receptor and Ibex for the B cell receptor. If you are interested in making your own deep-learning models with immune receptors, please see immApex.

Installation

Installation of Master Branch

immApex is now required for the underlying processes of scRepertoire make sure if not using bioconductor, to call both during installation.

remotes::install_github(c("BorchLab/immApex", "BorchLab/scRepertoire"))

Installing from Bioconductor

The current version of scRepertoire is also available on Bioconductor.

if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("scRepertoire")

Legacy Version 1

If you are looking for version 1 of scRepertoire - there is a static version available below:

devtools::install_github("ncborcherding/scRepertoire@v1")

Getting Data

Unfortunately, Github limits the size of individual files. In order to access the full Seurat object paired with scRepertoire please download the .rda from here. There is a smaller version of the cohort built into scRepertoire called scRep_example.

Please Cite

Version 2: Yang, Q, & Safina, K., Nguyen, K., Tuong, Z.K., & Borcherding, N. (2025). “scRepertoire 2: Enhanced and efficient toolkit for single-cell immune profiling.” PLoS Computational Biology https://doi.org/10.1371/journal.pcbi.1012760
Version 1: Borcherding, Nicholas, Nicholas L. Bormann, and Gloria Kraus. “scRepertoire: An R-based toolkit for single-cell immune receptor analysis.” F1000Research https://doi.org/10.12688/f1000research.22139.2

Bug Reports/New Features

GitHub issue

If possible please include a reproducible example. Alternatively, an example with the internal scRep_example and contig_list would be extremely helpful.

Features or Enhancements Requests

Pull Requests

All are welcome for bug fixes, new features, or enhancements.

Please set PR to merge with “dev” branch and provide description of what the PR contains (referencing existing issue(s) if appropriate).

Contact

Questions, comments, suggestions, please feel free to reach out via the GitHub Repository.

scRepertoire