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

Generation probability, diversity, and simulation for AIRR-seq TCR/BCR repertoires, from graph models of decomposed receptor sequences. Python, C-accelerated.

Comparison of gene usage in immune repertoires under different biological conditions

🦋 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

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.

Code-only downstream scRNA-seq plus scTCR-seq workflow for PBMC-style 10x multi-omic inputs, with reproducible steps and expected results structure.

Computes the standard diversity metrics — richness estimators, evenness indices, and dominance measures — for immune receptor repertoires and peptide libraries, with depth normalization so samples sequenced unevenly can be compared

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.