Boolean implication analysis unveils candidate universal relationships in microbiome data.

ABSTRACT:

Background

Microbiomes consist of bacteria, viruses, and other microorganisms, and are responsible for many different functions in both organisms and the environment. Past analyses of microbiomes focused on using correlation to determine linear relationships between microbes and diseases. Weak correlations due to nonlinearity between microbe pairs may cause researchers to overlook critical components of the data. With the abundance of available microbiome, we need a method that comprehensively studies microbiomes and how they are related to each other.

Results

We collected publicly available datasets from human, environment, and animal samples to determine both symmetric and asymmetric Boolean implication relationships between a pair of microbes. We then found relationships

SUBMITTER: Vo D 

PROVIDER: S-EPMC7863539 | biostudies-literature | 2021 Feb

REPOSITORIES: biostudies-literature