The application of network label propagation to rank biomarkers in genome-wide Alzheimer's data.

ABSTRACT:

Background

Ranking and identifying biomarkers that are associated with disease from genome-wide measurements holds significant promise for understanding the genetic basis of common diseases. The large number of single nucleotide polymorphisms (SNPs) in genome-wide studies (GWAS), however, makes this task computationally challenging when the ranking is to be done in a multivariate fashion. This paper evaluates the performance of a multivariate graph-based method called label propagation (LP) that efficiently ranks SNPs in genome-wide data.

Results

The performance of LP was evaluated on a synthetic dataset and two late onset Alzheimer's disease (LOAD) genome-wide datasets, and the performance was compared to that of three control methods. The control methods included chi squar

SUBMITTER: Stokes ME 

PROVIDER: S-EPMC4234455 | biostudies-literature | 2014 Apr

REPOSITORIES: biostudies-literature