Improved branch and bound algorithm for detecting SNP-SNP interactions in breast cancer.

ABSTRACT:

Background

Single nucleotide polymorphisms (SNPs) in genes derived from distinct pathways are associated with a breast cancer risk. Identifying possible SNP-SNP interactions in genome-wide case-control studies is an important task when investigating genetic factors that influence common complex traits; the effects of SNP-SNP interaction need to be characterized. Furthermore, observations of the complex interplay (interactions) between SNPs for high-dimensional combinations are still computationally and methodologically challenging. An improved branch and bound algorithm with feature selection (IBBFS) is introduced to identify SNP combinations with a maximal difference of allele frequencies between the case and control groups in breast cancer, i.e., the high/low risk combinations of

SUBMITTER: Chuang LY 

PROVIDER: S-EPMC3626712 | biostudies-literature | 2013 Feb

REPOSITORIES: biostudies-literature