Bag of Naive Bayes: biomarker selection and classification from genome-wide SNP data.

ABSTRACT:

Background

Multifactorial diseases arise from complex patterns of interaction between a set of genetic traits and the environment. To fully capture the genetic biomarkers that jointly explain the heritability component of a disease, thus, all SNPs from a genome-wide association study should be analyzed simultaneously.

Results

In this paper, we present Bag of Naïve Bayes (BoNB), an algorithm for genetic biomarker selection and subjects classification from the simultaneous analysis of genome-wide SNP data. BoNB is based on the Naïve Bayes classification framework, enriched by three main features: bootstrap aggregating of an ensemble of Naïve Bayes classifiers, a novel strategy for ranking and selecting the attributes used by each classifier in the ensemble and a permutation-ba

SUBMITTER: Sambo F 

PROVIDER: S-EPMC3439675 | biostudies-literature | 2012

REPOSITORIES: biostudies-literature