OmniCorr: an R-package for visualizing putative host-microbiome interactions using multi-omics data

TL;DR

OmniCorr is an R package that helps researchers visualize and analyze interactions between hosts and their microbiomes using multi-omics data.

Contribution

OmniCorr introduces a novel computational tool for integrating and visualizing host-microbiome interactions across multiple omics layers.

Findings

OmniCorr clusters co-varying features into modules to manage omics data complexity.

The package identifies statistically significant associations indicative of host-microbiome interactions.

OmniCorr's utility is demonstrated in studies of Atlantic salmon and cattle using diverse omics datasets.

Abstract

Holo-omics leverages omics datasets to explore the interactions between hosts and their associated microbiomes. Although the generation of omics data from matching host and microbiome samples is steadily increasing, there remains a scarcity of computational tools capable of integrating and visualizing this data to facilitate the prediction and interpretation of host-microbiome interactions. We present OmniCorr, an R package designed to: (i) manage the complexity of omics data by clustering co-varying features (e.g. genes, proteins, and metabolites) into modules, (ii) visualize correlations of these modules across different omics layers, host-microbiome interfaces, and metadata, and (iii) identify statistically significant associations indicative of putative host-microbiome interactions. OmniCorr’s utility is demonstrated using datasets from two systems: (i) Atlantic salmon, integrating host transcriptomics with metagenomics and metatranscriptomics to explore dietary impacts, and (ii) cattle, combining host proteomics with metaproteomics to investigate methane emission variability.

Availability and implementation: OmniCorr is freely available at https://github.com/shashank-KU/OmniCorr.

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