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ABSTRACT: Background
The Atlantic salmon gut constitutes an intriguing system for studying host-microbiota interactions due to the dramatic environmental change salmon experiences during its life cycle. Yet, little is known about the role of interactions in this system and there is a general deficit in computational methods for integrative analysis of omics data from host-microbiota systems.Methods
We developed a pipeline to integrate host RNAseq data and microbial 16S rRNA amplicon sequencing data using weighted correlation network analysis. Networks are first inferred from each dataset separately, followed by module detections and finally robust identification of interactions via comparisons of representative module profiles. Through the use of module profiles, this network-based d
SUBMITTER: Strand MA
PROVIDER: S-EPMC7876536 | biostudies-literature | 2021
REPOSITORIES: biostudies-literature