Discrimination of DNA Methylation Signal from Background Variation for Clinical Diagnostics.

ABSTRACT: Advances in the study of human DNA methylation variation offer a new avenue for the translation of epigenetic research results to clinical applications. Although current approaches to methylome analysis have been helpful in revealing an epigenetic influence in major human diseases, this type of analysis has proven inadequate for the translation of these advances to clinical diagnostics. As in any clinical test, the use of a methylation signal for diagnostic purposes requires the estimation of an optimal cutoff value for the signal, which is necessary to discriminate a signal induced by a disease state from natural background variation. To address this issue, we propose the application of a fundamental signal detection theory and machine learning approaches. Simulation studies and tests of

SUBMITTER: Sanchez R 

PROVIDER: S-EPMC6862328 | biostudies-literature | 2019 Oct

REPOSITORIES: biostudies-literature