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BACKGROUND:  Pediatric acute respiratory distress in tropical settings is very common. Bacterial pneumonia is a major contributor to morbidity and mortality and requires adequate diagnosis for correct treatment. A rapid test that could identify bacterial (vs. other) infections would have great clinical utility.

METHODS AND FINDINGS:  We performed RNA-Seq and analyzed the transcriptomes of 68 pediatric patients with well-characterized clinical phenotype to identify transcriptional features associated with each disease class. We refined the features to predictive models (support vector machine, elastic net) and validated those models on an independent test set of 37 patients (80 - 85% accuracy).

CONCLUSIONS:  We have identified sets of genes that are differentially expressed in pediatric patients with pneumonia syndrome attributable to different infections and requiring different therapeutic interventions. This study demonstrates that human transcription signatures in infected patients recapitulate the underlying biology and provide models for predicting a bacterial diagnosis to inform treatment.