Evidence map›Paper›PMID 41692950›Full record

ArticleBioinformatics (Oxford, England)2026

moiraine: an R package to construct reproducible pipelines for the application and comparison of multi-omics integration methods.

Olivia Angelin-Bonnet, Lindy Guo, Roy Storey, Susan Thomson

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Article in Bioinformatics (Oxford, England), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Olivia Angelin-BonnetData Science, Bioeconomy Science Institute, Palmerston North 4442, New Zealand.ORCID 0000-0002-7708-2919
Lindy GuoData Science, Bioeconomy Science Institute, Auckland 1142, New Zealand.ORCID 0000-0002-8666-2173
Roy StoreyKiwifruit New Cultivars, Bioeconomy Science Institute, Te Puke 3182, New Zealand.ORCID 0000-0003-1375-7136
Susan ThomsonMolecular & Digital Breeding, Bioeconomy Science Institute, Christchurch 8140, New Zealand.ORCID 0000-0001-7127-9414

Funding

New Zealand Institute for Plant and Food Research Limited
6 · The paper itself

Abstract

motivationIn the past decades, many statistical methods for integrating multi-omics data have been developed. They have been implemented into software tools, which differ widely in their programming choices, such as the format required for data input, or the format of the generated integration results. This lack of standards renders cumbersome and time-intensive the application and comparison of different integration tools to the same multi-omics dataset.

resultsWe have developed the moiraine R package for constructing reproducible multi-omics integration pipelines, which enables users to apply one or more statistical methods for multi-omics integration to their own multi-omics dataset. moiraine facilitates the preprocessing of the omics datasets and automates their formatting for the integration step. It simplifies the interpretation and evaluation of the integration results through the construction of visualizations in which metadata about samples and features can easily be included. Crucially, it enables the comparison of results obtained with different integration tools, allowing users to assess the robustness of their results. AVAILABILITY AND IMPLEMENTATION: The moiraine R package is publicly available at https://github.com/Plant-Food-Research-Open/moiraine; an archival snapshot of the package is available on Zenodo at https://doi.org/10.5281/zenodo.17172718. A detailed tutorial is available at https://plant-food-research-open.github.io/moiraine-manual/.

Indexed as

Computational BiologyGenomicsMultiomicsSoftware

Identifiers

PMID41692950
PMCPMC12960915

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.