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screpertoire

A toolkit for single-cell immune profiling

https://github.com/borchlab/screpertoire

Science Score: 57.0%

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Last synced: 7 months ago · JSON representation ·

Repository

A toolkit for single-cell immune profiling

Basic Info
Statistics
  • Stars: 342
  • Watchers: 12
  • Forks: 62
  • Open Issues: 2
  • Releases: 7
Created about 6 years ago · Last pushed 8 months ago
Metadata Files
Readme Changelog License Citation

README.md

scRepertoire: A toolkit for single-cell immune profiling

BioC status R-CMD-check Codecov test coverage Documentation <!-- badges: end -->

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 deep-learning-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.

Working with scRepertoire

scRepertoire has a comprehensive website for detailed tutorials and function information.

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.

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

Installing from Bioconductor

The current version of scRepertoire is also available on Bioconductor.

```R 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:

R devtools::install_github("BorchLab/scRepertoire@v1")

Getting Data

Unfortunately, Github limits the size of individual files. In order to access the Seurat object paired with scRepertoire please download the .rda from here.

Bug Reports/New Features

If you run into any issues or bugs please submit a GitHub issue with details of the issue.

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

Any requests for new features or enhancements can also be submitted as GitHub issues.

Pull Requests are welcome for bug fixes, new features, or enhancements.

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

If you are building your own tool based on scRepertoire, reach out, we are happy to help and make things compatible.

Owner

  • Name: BorchLab
  • Login: BorchLab
  • Kind: organization

Citation (CITATION.cff) 

cff-version: 1.2.0
title: scRepertoire
message: >-
  If you use this software, please cite it using the
  metadata from this file.
type: software
authors:
  - given-names: Qile
    family-names: Yang
    orcid: 'https://orcid.org/0009-0005-0148-2499'
    affiliation: 'UC Berkeley, Berkeley, CA, USA'
  - given-names: Ksenia R.
    family-names: Safina
    orcid: 'https://orcid.org/0000-0002-5126-9953'
    affiliation: 'Broad Institute of MIT and Harvard, Cambridge, MA, USA'
  - given-names: Kieu D. Q.
    family-names: Nguyen
    affiliation: >-
      Ian Frazer Centre for Children’s Immunotherapy
      Research, Child Health Research Centre, Faculty of
      Health, Medicine and Behavioural Sciences, The
      University of Queensland, AU
  - orcid: 'https://orcid.org/0000-0002-6735-6808'
    given-names: Zewen K.
    family-names: Tuong
    affiliation: >-
      Ian Frazer Centre for Children’s Immunotherapy
      Research, Child Health Research Centre, Faculty of
      Health, Medicine and Behavioural Sciences, The
      University of Queensland, AU
  - given-names: Nicholas
    family-names: Borcherding
    orcid: 'https://orcid.org/0000-0003-1427-6342'
    affiliation: >-
      Department of Pathology and Immunology, Washington
      University in St Louis, MO 63110, USA
    email: borcherding.n@wustl.edu
identifiers:
  - type: doi
    value: 10.1371/journal.pcbi.1012760
    description: PLOS Computational Biology Paper
repository-code: 'https://github.com/BorchLab/scRepertoire'
url: 'https://www.borch.dev/uploads/screpertoire/'
repository: >-
  https://bioconductor.org/packages/release/bioc/html/scRepertoire.html
abstract: >-
  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.
keywords:
  - T cells
  - Immune receptors
  - Immune response
  - Protein sequencing
  - Amino acid analysis
  - Amino acid sequence analysis
  - Transcriptome analysis
  - Cloning
license: MIT
version: 2.0.0
date-released: '2025-06-27'

GitHub Events

Total
  • Create event: 22
  • Release event: 2
  • Issues event: 55
  • Watch event: 22
  • Delete event: 7
  • Issue comment event: 90
  • Push event: 90
  • Pull request event: 30
  • Fork event: 4
Last Year
  • Create event: 22
  • Release event: 2
  • Issues event: 55
  • Watch event: 22
  • Delete event: 7
  • Issue comment event: 90
  • Push event: 90
  • Pull request event: 30
  • Fork event: 4

Issues and Pull Requests

Last synced: 7 months ago

All Time
  • Total issues: 33
  • Total pull requests: 18
  • Average time to close issues: 2 days
  • Average time to close pull requests: 6 days
  • Total issue authors: 26
  • Total pull request authors: 5
  • Average comments per issue: 1.64
  • Average comments per pull request: 0.44
  • Merged pull requests: 13
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 33
  • Pull requests: 18
  • Average time to close issues: 2 days
  • Average time to close pull requests: 6 days
  • Issue authors: 26
  • Pull request authors: 5
  • Average comments per issue: 1.64
  • Average comments per pull request: 0.44
  • Merged pull requests: 13
  • Bot issues: 0
  • Bot pull requests: 0
View more stats
Top Authors
Issue Authors
  • ncborcherding (6)
  • monikaramos (2)
  • pwmellors (2)
  • pm-Genome2021 (1)
  • airabiotenor (1)
  • SuleimanovShakir (1)
  • LynnChan99 (1)
  • zktuong (1)
  • kriegerm (1)
  • tumorscholar (1)
  • Chiranjit1504 (1)
  • Xiangyi-Deng (1)
  • thepope0 (1)
  • liezeltamon (1)
  • Junedays (1)
Pull Request Authors
  • ncborcherding (12)
  • mihem (2)
  • Qile0317 (2)
  • jreimertz (1)
  • zjsyj (1)
Top Labels
Issue Labels
enhancement (4) more info needed (4) bug (2)
Pull Request Labels
bug (1)

Packages

  • Total packages: 2
  • Total downloads: unknown
  • Total dependent packages: 0
    (may contain duplicates)
  • Total dependent repositories: 0
    (may contain duplicates)
  • Total versions: 14
proxy.golang.org: github.com/BorchLab/scRepertoire
  • Versions: 7
  • Dependent Packages: 0
  • Dependent Repositories: 0
Rankings
Dependent packages count: 5.5%
Average: 5.6%
Dependent repos count: 5.8%
Last synced: 7 months ago
proxy.golang.org: github.com/borchlab/screpertoire
  • Versions: 7
  • Dependent Packages: 0
  • Dependent Repositories: 0
Rankings
Dependent packages count: 5.5%
Average: 5.6%
Dependent repos count: 5.8%
Last synced: 7 months ago

Dependencies

DESCRIPTION cran
  • R >= 4.0 depends
  • ggplot2 * depends
  • SeuratObject * imports
  • SingleCellExperiment * imports
  • SummarizedExperiment * imports
  • doParallel * imports
  • dplyr * imports
  • ggalluvial * imports
  • ggraph * imports
  • igraph * imports
  • methods * imports
  • parallel * imports
  • plyr * imports
  • powerTCR * imports
  • reshape2 * imports
  • rlang * imports
  • stringdist * imports
  • stringr * imports
  • tidygraph * imports
  • utils * imports
  • vegan * imports
  • BiocStyle * suggests
  • Seurat * suggests
  • circlize * suggests
  • knitr * suggests
  • rmarkdown * suggests
  • scales * suggests
  • scater * suggests
.github/workflows/R-CMD-check.yaml actions
  • actions/checkout v3 composite
  • r-lib/actions/check-r-package v2 composite
  • r-lib/actions/setup-r v2 composite
  • r-lib/actions/setup-r-dependencies v2 composite
.github/workflows/pkgdown.yaml actions
  • JamesIves/github-pages-deploy-action v4.4.1 composite
  • actions/checkout v3 composite
  • r-lib/actions/setup-pandoc v2 composite
  • r-lib/actions/setup-r v2 composite
  • r-lib/actions/setup-r-dependencies v2 composite
.github/workflows/pr-commands.yaml actions
  • actions/checkout v3 composite
  • r-lib/actions/pr-fetch v2 composite
  • r-lib/actions/pr-push v2 composite
  • r-lib/actions/setup-r v2 composite
  • r-lib/actions/setup-r-dependencies v2 composite
.github/workflows/test-coverage.yaml actions
  • actions/checkout v3 composite
  • actions/upload-artifact v3 composite
  • r-lib/actions/setup-r v2 composite
  • r-lib/actions/setup-r-dependencies v2 composite