Cluster-based analysis, or community typing, has been attempted as a method for studying the human microbiome in various body niches with the aim of reducing variations in the bacterial composition and linking the defined communities to host health and disease. In this study, we have presented the bacterial subcommunities in the healthy and the diseased population cohorts and have assessed whether these subcommunities can distinguish different host health conditions.
We performed community typing analysis on the sputum microbiome dataset obtained from a healthy Korean twin-family cohort (
The analysis of the sputum microbiome of a healthy Korean cohort revealed high levels of interindividual variation, which was driven by two dominant bacteria:
Overall, our findings point to a potential association between pulmonary