Predicting nasal diseases based on microbiota relationship network.

ABSTRACT:

Objectives

Increasing evidence indicates that the local microbiome can be used to predict host disease states. However, constructing models that obtain better results with fewer features is still challenging.

Methods

In this study, we established a nasal microbiome database consisting of 132 chronic rhinosinusitis patients, 27 nasal inverted papilloma patients, and 45 control patients. 16S rRNA gene sequencing was used to identify the species and abundance of bacteria in each sample, and a nasal microbiome database was generated after low-abundance bacteria were eliminated. The correlation data network of different groups of bacteria was constructed by calculating the correlation coefficient among bacterial genera, and the correlation parameters of the network were calculate

SUBMITTER: Liang Y 

PROVIDER: S-EPMC11833901 | biostudies-literature | 2025 Jan-Mar

REPOSITORIES: biostudies-literature