A mixed-model approach for estimating drivers of microbiota community composition and differential taxonomic abundance.

ABSTRACT: Next-generation sequencing (NGS) and metabarcoding approaches are increasingly applied to wild animal populations, but there is a disconnect between the widely applied generalized linear mixed model (GLMM) approaches commonly used to study phenotypic variation and the statistical toolkit from community ecology typically applied to metabarcoding data. Here, we describe the suitability of a novel GLMM-based approach for analyzing the taxon-specific sequence read counts derived from standard metabarcoding data. This approach allows decomposition of the contribution of different drivers to variation in community composition (e.g., age, season, individual) via interaction terms in the model random-effects structure. We provide guidance to implementing this approach and show how these models can

SUBMITTER: Sweeny AR 

PROVIDER: S-EPMC10469806 | biostudies-literature | 2023 Aug

REPOSITORIES: biostudies-literature