Boolean analysis reveals systematic interactions among low-abundance species in the human gut microbiome.

ABSTRACT: The analysis of microbiome compositions in the human gut has gained increasing interest due to the broader availability of data and functional databases and substantial progress in data analysis methods, but also due to the high relevance of the microbiome in human health and disease. While most analyses infer interactions among highly abundant species, the large number of low-abundance species has received less attention. Here we present a novel analysis method based on Boolean operations applied to microbial co-occurrence patterns. We calibrate our approach with simulated data based on a dynamical Boolean network model from which we interpret the statistics of attractor states as a theoretical proxy for microbiome composition. We show that for given fractions of synergistic and competiti

SUBMITTER: Claussen JC 

PROVIDER: S-EPMC5480827 | biostudies-literature | 2017 Jun

REPOSITORIES: biostudies-literature