Differential variability improves the identification of cancer risk markers in DNA methylation studies profiling precursor cancer lesions | Zendy

Andrew E. Teschendorff | Zendy; Martin Widschwendter | Zendy

Open Access

Differential variability improves the identification of cancer risk markers in DNA methylation studies profiling precursor cancer lesions

Author(s) -

Andrew E. Teschendorff,

Martin Widschwendter

Publication year - 2012

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/bts170

Subject(s) - dna methylation , biology , epigenetics , methylation , computational biology , carcinogenesis , gene expression profiling , genetics , bioinformatics , cancer , gene , gene expression

The standard paradigm in omic disciplines has been to identify biologically relevant biomarkers using statistics that reflect differences in mean levels of a molecular quantity such as mRNA expression or DNA methylation. Recently, however, it has been proposed that differential epigenetic variability may mark genes that contribute to the risk of complex genetic diseases like cancer and that identification of risk and early detection markers may therefore benefit from statistics based on differential variability.

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