A1 Refereed original research article in a scientific journal
HoloFoodR: a statistical programming framework for holo-omics data integration workflows
Authors: Borman, Tuomas; Sannikov, Artur; Finn, Robert D; Limborg, Morten Tønsberg; Rogers, Alexander B; Kale, Varsha; Hanhineva, Kati; Lahti, Leo
Editors: Kendziorski Christina
Publisher: Oxford University Press (OUP)
Publication year: 2025
Journal: Bioinformatics
Article number: btaf605
ISSN: 1367-4803
eISSN: 1367-4811
DOI: https://doi.org/10.1093/bioinformatics/btaf605
Publication's open availability at the time of reporting: Open Access
Publication channel's open availability : Open Access publication channel
Web address : https://doi.org/10.1093/bioinformatics/btaf605
Self-archived copy’s web address: https://research.utu.fi/converis/portal/detail/Publication/505305696
Summary: 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.
Availability and implementation: 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.
Supplementary information: Available in the package vignette https://ebi-metagenomics.github.io/HoloFoodR/articles/case_study.html.
Keywords: bioconductor; data integration; holo-omics; metabolomics; metagenomics; multi-omics.
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Funding information in the publication:
This work was supported by the European Commission in the framework of the Horizon2020 Project FindingPheno [GA 952914] and HoloFood [GA 817729]. L.L. was supported by Research Council of Finland [grant number 330887]. A.S. and K.H. were supported by Jane and Aatos Erkko Foundation and the Research Council of Finland [grant numbers 321716, 334814]. M.T.L. was supported by the Danish National Research Foundation [grant DNRF143].
