Summary
Min et al. (2018) present meffil, an R package designed to address computational challenges in analysing large-scale DNA methylation datasets from Illumina BeadChip microarrays. The software implements an optimised functional normalisation algorithm that reduces computational memory without sacrificing speed, incorporates fixed and random effects to minimise technical variation, and supports federated analysis across geographically distributed datasets. The approach improves statistical power whilst reducing false positive rates in epigenome-wide association studies.
UK applicability
As a methodological tool for DNA methylation analysis, meffil may have broad applicability to UK-based epigenomic research initiatives, including cohort studies and biobank projects. Its capacity for distributed analysis is particularly relevant to large-scale UK research consortia that seek to harmonise methylation data across multiple sites.
Key measures
Computational memory requirements, processing time, technical variation in DNA methylation levels, false positive rates, statistical power in epigenome-wide association studies
Outcomes reported
The study describes development and validation of meffil, an R package for quality control, normalisation and epigenome-wide association studies of large DNA methylation datasets from Illumina microarrays. The package reduces technical variation in methylation measurements and enables distributed analysis across multiple sites without sharing individual-level data.
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