A supervised learning method for classifying methylation disorders.

ABSTRACT:

Background

DNA methylation is one of the most stable and well-characterized epigenetic alterations in humans. Accordingly, it has already found clinical utility as a molecular biomarker in a variety of disease contexts. Existing methods for clinical diagnosis of methylation-related disorders focus on outlier detection in a small number of CpG sites using standardized cutoffs which differentiate healthy from abnormal methylation levels. The standardized cutoff values used in these methods do not take into account methylation patterns which are known to differ between the sexes and with age.

Results

Here we profile genome-wide DNA methylation from blood samples drawn from within a cohort composed of healthy controls of different age and sex alongside patients with Prader-Willi

SUBMITTER: Walsh JR 

PROVIDER: S-EPMC10863277 | biostudies-literature | 2024 Feb

REPOSITORIES: biostudies-literature