Phenotype prediction based on genome-wide DNA methylation data.

ABSTRACT:

Background

DNA methylation (DNAm) has important regulatory roles in many biological processes and diseases. It is the only epigenetic mark with a clear mechanism of mitotic inheritance and the only one easily available on a genome scale. Aberrant cytosine-phosphate-guanine (CpG) methylation has been discussed in the context of disease aetiology, especially cancer. CpG hypermethylation of promoter regions is often associated with silencing of tumour suppressor genes and hypomethylation with activation of oncogenes.Supervised principal component analysis (SPCA) is a popular machine learning method. However, in a recent application to phenotype prediction from DNAm data SPCA was inferior to the specific method EVORA.

Results

We present Model-Selection-SPCA (MS-SPCA), an enhance

SUBMITTER: Wilhelm T 

PROVIDER: S-EPMC4073816 | biostudies-literature | 2014 Jun

REPOSITORIES: biostudies-literature