Disentangling environmental effects in microbial association networks.

ABSTRACT:

Background

Ecological interactions among microorganisms are fundamental for ecosystem function, yet they are mostly unknown or poorly understood. High-throughput-omics can indicate microbial interactions through associations across time and space, which can be represented as association networks. Associations could result from either ecological interactions between microorganisms, or from environmental selection, where the association is environmentally driven. Therefore, before downstream analysis and interpretation, we need to distinguish the nature of the association, particularly if it is due to environmental selection or not.

Results

We present EnDED (environmentally driven edge detection), an implementation of four approaches as well as their combination to predict whi

SUBMITTER: Deutschmann IM 

PROVIDER: S-EPMC8620190 | biostudies-literature | 2021 Nov

REPOSITORIES: biostudies-literature