Integrated Multi-Omics and Machine Learning for Tuberculosis Diagnostic Biomarker Discovery

This repository includes metadata files, raw data and processed data for 3 cohorts in the study by Tien NTN and Yen NTH et al. The study associated with this data repository employed an integrative multi-omics approach combined with predictive machine learning modeling to identify and validate circulating immunometabolic biomarkers that differentiate active tuberculosis (TB) from nontuberculous mycobacteria (NTM) infections, latent TB infection (LTBI), and other lung diseases (ODx).