Predicting antimicrobial resistance in Pseudomonas aeruginosa with machine learning-enabled molecular diagnostics

Datasets for manuscript "Predicting antimicrobial resistance in Pseudomonas aeruginosa with machine learning-enabled molecular diagnostics" <strong>Metadata.zip</strong> <strong>phenotypes.txt: </strong>tabular file containing binary resistance phenotypes based on CLSI guidelines, where the rows are the isolates and the columns correspond to different drugs. Resistance : 1, susceptibility: 0, missing: intermediate resistant <strong>Features_gpa_exp_snps.zip </strong> <strong>genexp</strong>: gene expression table directory genexp_feature_vect.npz: The feature matrix in the numpy format genexp_feature_list.txt: The columns of the feature matrix (features) genexp_strains_list.txt: The rows of the feature matrix (isolates) <strong>gpa: </strong>gene presence/absence table directory gpa_feature_vect.npz: The feature matrix in the numpy format gpa_feature_list.txt: The columns of the feature matrix (features) gpa_strains_list.txt: The rows of the feature matrix (isolates) <strong>snps: </strong>SNPs table directory snps_feature_vect.npz: The feature matrix in the numpy format snps_feature_list.txt: The columns of the feature matrix (features) snps_strains_list.txt: The rows of the feature matrix (isolates)