TCR/BCR repertoire analysis — Pgen/generation/inference, diversity, overlap, biomarkers (Python + C++)
Project description
vdjtools 2.0
TCR/BCR immune-repertoire analysis — a clean-room Python + C++ rewrite of the legacy Groovy/Java vdjtools, standardised on the AIRR schema and polars DataFrames with minimal object-orientation.
Built on the antigenomics ecosystem: seqtree (fuzzy search / e-value engine), vdjmatch (overlap + TCRnet), arda (AIRR annotation + markup repair).
Status: v2.0.0 under active development. The legacy v1.x tool lives on the
legacy-1.xbranch and its releases remain available under the repository tags (v0.0.1…1.2.1).
Capabilities (rolling out by phase — see ROADMAP.md)
- Model — native V(D)J recombination model: generation probability (Pgen), sequence generation, and EM model inference. Supersedes OLGA and IGoR: arda-driven scenario enumeration, polars marginal tables, D-D tandem support, and a native (pybind11) Pgen/EM core.
- Stats — diversity (Chao1/Shannon/Simpson/…), spectratype, V/J/VJ usage.
- Features — CDR physicochemical profiles, k-mer / V+k-mer summaries.
- Overlap — sample overlap and TCRnet (via vdjmatch/seqtree).
- Preprocess — downsampling, error-correction, VJ-usage batch-effect correction, pooling/joining.
- Biomarker — incidence-based association (Fisher) vs HLA / condition / chain-pairing; metaclonotypes.
- Single-cell — AIRR Cell / 10x interoperability.
Install
conda env create -f environment.yml # python + mmseqs2 (arda backend) + C++ toolchain
conda activate vdjtools
pip install -e ".[dev,test]" # builds the _core C++ extension
Or run the bootstrap script: bash setup.sh --dev-parents --tests.
Pure-analytics use (diversity / spectratype / usage) does not require MMseqs2; the model and annotation paths do (via arda).
License
GPL-3.0-or-later.
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