Systematic comparison of published host gene expression signatures for bacterial/viral discrimination

Nicholas Bodkin, Melissa Ross, Micah T. McClain, Emily R. Ko, Christopher W. Woods, Geoffrey S. Ginsburg, Ricardo Henao, Ephraim L. Tsalik

Research output: Contribution to journalArticlepeer-review

16 Scopus citations

Abstract

Background: Measuring host gene expression is a promising diagnostic strategy to discriminate bacterial and viral infections. Multiple signatures of varying size, complexity, and target populations have been described. However, there is little information to indicate how the performance of various published signatures compare to one another. Methods: This systematic comparison of host gene expression signatures evaluated the performance of 28 signatures, validating them in 4589 subjects from 51 publicly available datasets. Thirteen COVID-specific datasets with 1416 subjects were included in a separate analysis. Individual signature performance was evaluated using the area under the receiving operating characteristic curve (AUC) value. Overall signature performance was evaluated using median AUCs and accuracies. Results: Signature performance varied widely, with median AUCs ranging from 0.55 to 0.96 for bacterial classification and 0.69–0.97 for viral classification. Signature size varied (1–398 genes), with smaller signatures generally performing more poorly (P < 0.04). Viral infection was easier to diagnose than bacterial infection (84% vs. 79% overall accuracy, respectively; P
Original languageEnglish (US)
JournalGenome Medicine
Volume14
Issue number1
DOIs
StatePublished - Dec 1 2022
Externally publishedYes

Bibliographical note

Generated from Scopus record by KAUST IRTS on 2023-02-15

ASJC Scopus subject areas

  • Genetics
  • Molecular Biology
  • Molecular Medicine
  • Genetics(clinical)

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