Genomic virulence biomarkers in Pseudomonas aeruginosa bloodstream infection
Description
Code and microbiological data to generate the main findings of the study: "Genomic markers of virulence in Pseudomonas aeruginosa is associated with mortality and septic shock in patients with bloodstream infection". No legal responsibility or warranty comes with the scripts or data. Contact: john.karlsson.valik@ki.se
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Steps to reproduce
LIST OF DATA: Shared data comprises annotated microbiological data, resistance phenotype data and source data to generate the main figures. Due to legal restrictions, individual patient-level data cannot be shared. For enquirers regarding the code or output, feel free to contact me. LIST OF DATA a). merge_large_git.xlsx - annotated microbiological and resitance phenotype data b). fig2_source_data.xlsx c). fig3a_source_data.xlsx d). fig3b_source_data.xlsx e). fig3c_source_data.xlsx f). fig4a_source_data.xlsx g). fig4b_source_data.xlsx h). fig5a_source_data.xlsx i). fig5b_source_data.xlsx j). fig6abc_source_data.xlsx k). fig6d_source_data.xlsx l). fig6ef_source_data.xlsx LIST OF R-SCRIPTS: 1.) table_1_git.R - code to generate Table 1 2.) PCoA_script_git.R - code to generate clusters and create Figure 4a. NOTE! The clusters are used in subsequent code 3.) phylogenetic_tree_git.R - code to generate the evolutionary tree and create Figure 3a 4.) graph_script_git.R - code to create Figures 2, 3b, 3c, 4b, 5a, and 5b 5.) modelling_git.R - code to generate statistics, logistic regression and create Figure 6a-c 6.) prediction_git.R - code to run the machine learning models and create Figure 6d-f