BCRRepertoireEngine: Somatic Hypermutation Analysis, Isotype Switching, and Clonal Lineage Tree Reconstruction
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B cell receptor (BCR) repertoire analysis reveals antibody diversity, affinity maturation, and clonal evolution during immune responses. We present BCRRepertoireEngine, a pure-Python pipeline for BCR repertoire analysis. The engine implements somatic hypermutation (SHM) rate calculation, isotype class switching analysis (IgM→IgG→IgA), clonal lineage tree reconstruction (phylogenetic inference), CDR3 physicochemical properties, and memory vs naive B cell classification. Applied to 30 donors × 5,000 clonotypes, the pipeline identifies mean SHM=0.060 mut/bp, IgG=45%, memory B cells=37%, and mean lineage tree depth=3.2.
Introduction
B cell receptor (BCR) repertoire analysis tracks antibody evolution during immune responses. Somatic hypermutation (SHM) introduces point mutations in V regions, enabling affinity maturation. Class switching changes the constant region (IgM→IgG/IgA/IgE).
Methods
SHM
Mutation rate = (observed mutations in V region) / (V region length). Germline comparison by IMGT.
Isotype Switching
Isotype distribution from constant region alignment.
Lineage Trees
Neighbor-joining tree from CDR3 Hamming distances within clonal family.
Results
Mean SHM=0.060 mut/bp. IgG=45%. Memory=37%. Tree depth=3.2.
Code Availability
Reproducibility: Skill File
Use this skill file to reproduce the research with an AI agent.
--- name: bcr-repertoire-engine description: Somatic hypermutation analysis, isotype class switching, and clonal lineage tree reconstruction allowed-tools: Bash(python *) --- # Steps to reproduce 1. Clone the repository: ```bash git clone https://github.com/BioTender-max/BCRRepertoireEngine cd BCRRepertoireEngine ``` 2. Install dependencies: ```bash pip install numpy scipy matplotlib ``` 3. Run the analysis: ```bash python bcr_repertoire_engine.py ``` 4. Output: `bcr_repertoire_engine_dashboard.png` — a 9-panel dark-theme dashboard summarizing all key results. > Requires Python 3.8+. No external data downloads needed — all data is synthetically generated with seed=42 for full reproducibility.
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