HoloFoodR: a statistical programming framework for holo-omics data integration workflows

TL;DR

HoloFoodR is a new R package that helps researchers integrate and analyze complex holo-omics data from hosts and their microbiomes.

Contribution

The novel contribution is the development of an open-source statistical framework for holo-omics data integration.

Findings

HoloFoodR provides a reproducible workflow for holo-omics data analysis.

The package is built on curated datasets like HoloFood, which contains 10,000 profiles.

It bridges the gap between data resources and algorithmic frameworks in holo-omics.

Abstract

Holo-omics is an emerging research area that integrates multi-omic datasets from the host organism and its microbiome to study their interactions. Recently, curated and openly accessible holo-omic databases have been developed. The HoloFood database, for instance, provides nearly 10 000 holo-omic profiles for salmon and chicken under controlled treatments. However, bridging the gap between holo-omic data resources and algorithmic frameworks remains a challenge. Combining the latest advances in statistical programming with curated holo-omic data sets can facilitate the design of open and reproducible research workflows in the emerging field of holo-omics.

HoloFoodR R/Bioconductor package and the source code are available under the open-source Artistic License 2.0 at the package homepage https://doi.org/10.18129/B9.bioc.HoloFoodR.

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