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

Abstract

<p><b>Summary:</b> 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.</p><p><b>Availability and implementation:</b> 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.</p><p><b>Supplementary information:</b> Available in the package vignette https://ebi-metagenomics.github.io/HoloFoodR/articles/case_study.html.</p><p><b>Keywords:</b> bioconductor; data integration; holo-omics; metabolomics; metagenomics; multi-omics.</p>