A SuperLearner-based pipeline for the development of DNA methylation-derived predictors of phenotypic traits.
<h4>Background</h4>DNA methylation (DNAm) provides a window to characterize the impacts of environmental exposures and the biological aging process. Epigenetic clocks are often trained on DNAm using penalized regression of CpG sites, but recent evidence suggests potential benefits of tra...
Saved in:
Main Authors: | Dennis Khodasevich, Nina Holland, Lars van der Laan, Andres Cardenas |
---|---|
Format: | Article |
Language: | English |
Published: |
Public Library of Science (PLoS)
2025-02-01
|
Series: | PLoS Computational Biology |
Online Access: | https://doi.org/10.1371/journal.pcbi.1012768 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Comparison of Super Resolution Reconstruction Acquisition Geometries for Use in Mouse Phenotyping
by: Niranchana Manivannan, et al.
Published: (2013-01-01) -
WTO, an ontology for wheat traits and phenotypes in scientific publications
by: Claire Nédellec, et al.
Published: (2020-06-01) -
Pre-operative DNA methylation marks as predictors of weight loss outcomes after sleeve gastrectomy
by: Guillermo Paz-López, et al.
Published: (2025-02-01) -
Genotype by environment interactions and phenotypic traits stability of the EUCLEG faba bean collection
by: Dejan Sokolović, et al.
Published: (2025-01-01) -
A phenotype-based AI pipeline outperforms human experts in differentially diagnosing rare diseases using EHRs
by: Xiaohao Mao, et al.
Published: (2025-01-01)