immune-repertoire

🧬 immunarch [R package] – Multi-Modal Immune Repertoire Analytics for Immunotherapy and Vaccine Design

immuneML is a platform for machine learning analysis of adaptive immune receptor repertoire data.

🦠 List of publicly available datasets with single-cell (scRNAseq) and T-cell/antibody immune repertoire (AIRR / RepSeq / immunosequencing) data of COVID-19 patients with SARS-CoV-2.

Comparison of Adaptive Immune Receptor Repertoires

Visualize clonal expansion via circle-packing. 'APackOfTheClones' extends 'scRepertoire' to produce a publication-ready visualization of clonal expansion at a single cell resolution, by representing expanded clones as differently sized circles.

BASIC: BCR and TCR assembly from single cell RNA-seq

Fast simulator of BCR and TCR sequences with full ground-truth annotations: V(D)J recombination, somatic hypermutation and sequencing artifacts across 23 species. Rust core with a Python API, for training and benchmarking AIRR-seq tools.

Alignment-free graph models of TCR and BCR repertoires built from Lempel-Ziv and FlashBack string decompositions. Compute sequence generation probability (Pgen) and repertoire diversity, and generate new sequences. Python with a C core.

Comparison of gene usage in immune repertoires under different biological conditions

Deep-learning V(D)J aligner for BCR and TCR sequences. A single model predicts V/D/J allele calls, segment boundaries and the junction, with AIRR-format output. Published in Nucleic Acids Research (2025).

🦋 immundata [R package] – A Unified Data Layer for Large-Scale Single-Cell, Spatial and Bulk Immunomics

Extract TCR and BCR clonotypes from raw sequencing data. Alignment against germline gene databases, error correction, receptor assembly, and clonotype grouping — turning FASTQ into a quantified repertoire with full QC.

Immunogenomics of pediatric nervous system tumours

Suit of statistical procedures for robust quantification of various BCR and TCR repertoire properties

🤖 AIRR-GPT is your intelligent guide for working with bulk and single-cell Adaptive Immune Receptor Repertoire (AIRR) data using immunarch and immundata R packages

Bioinformatic pipeline used to preprocess adaptive immune receptor repertoire sequencing raw reads into standardised AIRR-format for machine learning analysis

Minimal immune repertoire analysis pipeline using Change-O data to calculate clone diversity metrics (Shannon, Simpson) and visualize B-cell clonal distributions. Built in R.

Calculates V and J gene segment usage frequencies across samples, plus their pairwise combinations, revealing the germline biases that antigen exposure, vaccination, and disease leave behind.

Matches clonotypes between two V(D)J datasets — typically a deep bulk dataset and a smaller single-cell reference — so any property from the reference becomes available on the matched bulk clonotypes.