Figure 1 | Scientific Reports

Figure 1

From: Host-response transcriptional biomarkers accurately discriminate bacterial and viral infections of global relevance

Figure 1

Performance of GF-B/V model to classify bacterial and viral disease in a global cohort. (A) A binary model (GF-B/V) provides a single score that discriminates bacterial from viral infection. High probabilities closer to 1 are associated with bacterial infection and low probabilities closer to 0 indicate viral infection. (B) AUROC curve of the discovery cohort (RNA sequencing) for GF-B/V model. (C) AUROC curve of the validation cohort (NanoString platform) for GF-B/V model. (D) Predicted probabilities for the GF-B/V model in the discovery cohort for bacterial pathogens (blue) compared to viral pathogens (orange) using RNA sequencing. (E) Predicted probabilities for the GF-B/V model in the discovery cohort for bacterial pathogens (blue) compared to viral pathogens (orange) using NanoString assay. Bacterial abbreviations: Gram negative bacilli = Escherichia coli, Klebsiella pneumoniae, Rickettsia spp. = Spotted fever group, Typhus group, Orientia tsutsugamushi. Viral abbreviations: Other Resp. Virus = human Rhinovirus, Parainfluenza, human Metapneumovirus, Respiratory Syncytial Virus.

Back to article page