G

Gröschel, MI, Owens, M, Freschi, L, Vargas, R, Marin, MG, Phelan, J, Iqbal, Z, Dixit, A and Farhat, MR (2021). Additional file 1 of GenTB: A user-friendly genome-based predictor for tuberculosis resistance powered by machine learning. [Data Collection]. Figshare. https://doi.org/10.6084/m9.figshare.16544185.v1

N

Naker, K (2020). Mongolia MDR-TB contact e-registry ODK 2017. [Data Collection]. Open Science Framework. https://doi.org/10.17605/OSF.IO/N925X

P

Phelan, J, O’Sullivan, DM, Machado, D, Ramos, J, Oppong, YE, Campino, S, O’Grady, J, McNerney, R, Hibberd, ML, Viveiros, M, Huggett, JF and Clark, TG (2019). Additional file 1: of Integrating informatics tools and portable sequencing technology for rapid detection of resistance to anti-tuberculous drugs. [Data Collection]. Figshare. https://doi.org/10.6084/m9.figshare.8318861.v1

S

Senghore, M, Otu, J, Witney, A, Gehre, F, Doughty, EL, Kay, GL, Butcher, P, Salako, K, Kehinde, A, Onyejepu, N, Idigbe, E, Corrah, T, de Jong, B, Pallen, MJ and Antonio, M (2017). Whole-genome sequencing illuminates the evolution and spread of multidrug-resistant tuberculosis in Southwest Nigeria. [Data Collection]. PLOS ONE. https://doi.org/10.1371/journal.pone.0184510.s001

Sweeney, S and Kitson, N (2020). TB-Practecal economic evaluation sub-study: Data collection tools. [Data Collection]. London School of Hygiene & Tropical Medicine, London, United Kingdom. https://doi.org/10.17037/DATA.00001799.