Benchmarking High-Dimensional Mediation Methods in Epigenome-Wide Studies

Clicks: 3
ID: 338268
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
Emerging

Ranked #172 of 172 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 172 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 High-dimensional mediation analysis is increasingly used in omics studies to investigate molecular mediators of exposure–outcome relationships. In epigenome-wide studies, the number of CpG sites often greatly exceeds the sample size, while strong correlations among sites challenge reliable mediator selection and effect estimation. We systematically benchmarked four high-dimensional mediation methods—HIMA, HIMA2, HDMA, and a strategy combining high-dimensional mediation testing with stepwise regression (HDMTS)—under simulation settings varying signal strength, correlation structure, and the mediator-to-sample ratio (p/N). Results HIMA and HDMA consistently provided stringent false discovery proportion (FDP) control, whereas HIMA2 generally controlled FDP, with some inflation observed when the p/N ratio was high and mediator errors were independent. HDMTS showed greater sensitivity but exhibited reduced FDP control, particularly when mediator–outcome associations were weak and residual correlations among mediators were strong. Application to epigenome-wide DNA methylation data further demonstrated differences in mediator selection across methods and identified biologically plausible candidate mediators. Overall, our results highlight important trade-offs among false discovery control, sensitivity, and estimation accuracy and provide practical guidance for selecting high-dimensional mediation methods in epigenome-wide studies. Availability and implementation The HDMTS code is available at https://github.com/WanYuLin/HDMTS, and the simulation code is available at https://github.com/WanYuLin/HDMTS/tree/main/Simulations.
Reference Key
openalex_W7225091920 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Lin Wan-Yu
Are you one of these authors? Claim your profile
Journal Bioinformatics advances
Year 2026
DOI
10.1093/bioadv/vbag331
URL
https://doi.org/10.1093/bioadv/vbag331
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.