tidyexposomics: integrated exposure-omics analysis powered by tidy principles

Clicks: 20
ID: 324335
2026
Free PDF
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This article has not been analysed, so there is no overall score — reader engagement is measured and shown alongside.
AI Quality Assessment
Not analyzed
Readership in this journal
Steady

Ranked #124 of 183 articles by views in Bioinformatics advances

Most read Least read

Bar heights use a square-root scale. Only the 120 most-read articles are drawn; the journal has 183 in total.

Mint this article as an NFT
Not yet minted

Create a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.

5 SUSD one-off · no wallet required
Sign in to mint
Abstract
Abstract Motivation Environmental exposures shape health across the life course, influencing molecular pathways, disease susceptibility, and therapeutic response. However, integrating exposome and multi-omics data poses several challenges, ranging from extensive analytical steps to ensuring trends are consistent across studies. Results To address this challenge, we developed tidyexposomics, an open-source R package that delivers an end-to-end, tidyverse-native workflow including ontology-based exposure annotation, quality control, association testing, stability assessment, multi-omics integration, network analysis, and functional enrichment. The package offers intuitive Application Programming Interface (API), modular functions, and extensive visualization tools to facilitate flexible analyses. Comprehensive analytical step tracking and result export functions enable reproducibility and consistent reporting of downstream results. By combining systematic preprocessing, statistical modeling and biologically informed interpretation in one package, tidyexposomics streamlines exposure-omics analysis. Availability and implementation The GitHub repository for tidyexposomics is available at: https://github.com/BioNomad/tidyexposomics Pre-processed example data are available at: https://doi.org/10.5281/zenodo.17049350
Reference Key
openalex_W7201982247 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Jason Laird, Thomas Hartung, Fenna C M Sillé, Alexandra Maertens
Are you one of these authors? Claim your profile
Journal Bioinformatics advances
Year 2026
DOI
10.1093/bioadv/vbag220
URL
https://doi.org/10.1093/bioadv/vbag220
Keywords Keywords not found

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

Comments

No comments yet. Be the first to comment on this article.