Machine learning and phylogenetic analysis allow for predicting antibiotic resistance in M. tuberculosis.

Genome-wide association studies (GWAS) methods like linear mixed models accounts for the evolutionary relationships in bacteria, but they uncover only highly significant variants which have already been reported in literature.

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