Global tests of P-values for multifactor dimensionality reduction models in selection of optimal number of target genes.

ABSTRACT:

Background

Multifactor Dimensionality Reduction (MDR) is a popular and successful data mining method developed to characterize and detect nonlinear complex gene-gene interactions (epistasis) that are associated with disease susceptibility. Because MDR uses a combinatorial search strategy to detect interaction, several filtration techniques have been developed to remove genes (SNPs) that have no interactive effects prior to analysis. However, the cutoff values implemented for these filtration methods are arbitrary, therefore different choices of cutoff values will lead to different selections of genes (SNPs).

Methods

We suggest incorporating a global test of p-values to filtration procedures to identify the optimal number of genes/SNPs for further MDR analysis and demonstrate

SUBMITTER: Dai H 

PROVIDER: S-EPMC3508622 | biostudies-literature | 2012 May

REPOSITORIES: biostudies-literature