Abstract
Targeted sequencing of 16S rRNA genes enables the analysis of microbiomes. Here, we describe a protocol for the collection, storage, and preparation of fecal samples. We describe how we cluster similar sequences and assign bacterial taxonomies. Using diversity analysis and machine learning, we can extract disease-associated features. We also describe a circadian analysis to identify the presence or absence of rhythms in taxonomies. Differences in rhythmicity between cohorts can contribute to determining disease-associated bacterial signatures. For complete details on the use and execution of this protocol, please refer to Reitmeier et al. (2020).