Leveraging locus-specific epigenetic heterogeneity to improve the performance of blood-based DNA methylation biomarkers.

ABSTRACT:

Background

Variation in intercellular methylation patterns can complicate the use of methylation biomarkers for clinical diagnostic applications such as blood-based cancer testing. Here, we describe development and validation of a methylation density binary classification method called EpiClass (available for download at https://github.com/Elnitskilab/EpiClass ) that can be used to predict and optimize the performance of methylation biomarkers, particularly in challenging, heterogeneous samples such as liquid biopsies. This approach is based upon leveraging statistical differences in single-molecule sample methylation density distributions to identify ideal thresholds for sample classification.

Results

We developed and tested the classifier using reduced representation bisul

SUBMITTER: Miller BF 

PROVIDER: S-EPMC7574234 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature