TCR Clonality Analysis
Analyzed publicly available bulk TCR-β sequencing data to test whether repertoire clonality and M. tuberculosis-specific clonotype frequency differ between TB progressors and controllers. The workflow imports Adaptive-format repertoires with tcrdist3, standardizes V/J/CDR3 nomenclature to IMGT format, and cross-references experimental repertoires against curated IEDB and VDJdb reference sets to flag TB-specific clonotypes. From there it computes total and antigen-specific clonality (1 - normalized Shannon entropy) and TB-specific template frequency, then statistically compares the two cohorts.
Across these metrics, the analysis found no strong correlation between TCR-β clonality or TB-specific frequency and progressor/controller status, suggesting that clonality alone is insufficient to stratify M. tuberculosis infection trajectory in this cohort.
Platforms & Tools: Python, Jupyter, tcrdist3, pandas, NumPy, SciPy, seaborn, Conda
Source data drawn from Musvosvi et al., Nature Medicine (2022). Methodology mirrors prior work published in Frontiers in Immunology. Notebook source lives in bioinformatics-public/tcr_analysis.