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The comprehension of the microbial composition in upper respiratory tract infections is pivotal for the progression of diagnostic and treatment methodologies. This article presents a dataset derived from Precision Metagenomic next-generation sequencing using hybridization capture-based targeted sequencing. Nasopharyngeal samples from 24 patients with acute URIs were analyzed using the Illumina^®/IDbyDNA Respiratory Pathogen ID/AMR panel. The dataset contains a wealth of information on the composition of the microbiota, including the relative abundance of known pathogens and their potential clinical significance.

This dataset serves as a valuable asset for future research in respiratory medicine, infectious disease epidemiology, antimicrobial resistance detection, and therapeutic interventions. Its potential for reuse and integration with other omics datasets enhances its significance. The comprehensive nature of the data facilitates research into relationships between the respiratory microbiota and host factors, including clinical outcomes, immune responses, or genetic predispositions. Moreover, the article underscores the interdisciplinary potential by advocating for the integration of this dataset with other relevant datasets such as transcriptomics or metabolomics, enabling a deeper understanding of the intricate interactions in acute upper respiratory infections. The presented dataset contributes to the expanding knowledge in precision metagenomics and holds the promise to propel research and clinical practices in the field of respiratory diseases.