Small Ancestry Informative Marker panels for complete classification between the original four HapMap populations.

A protocol for the identification of Ancestry Informative Markers (AIMs) from genome-wide Single Nucleotide Polymorphism (SNP) data is proposed. The protocol consists of three main steps: identification of potential positive selection regions via F(ST) extremity measurement, SNP screening via two-stage attribute selection and classification model construction using a Naïve Bayes classifier. The two-stage attribute selection is composed of a newly developed round robin Symmetrical Uncertainty (SU) ranking technique and a wrapper embedded with a Naïve Bayes classifier.

An omnibus permutation test on ensembles of two-locus analyses can detect pure epistasis and genetic heterogeneity in genome-wide association studies.

This article presents the ability of an omnibus permutation test on ensembles of two-locus analyses (2LOmb) to detect pure epistasis in the presence of genetic heterogeneity. The performance of 2LOmb is evaluated in various simulation scenarios covering two independent causes of complex disease where each cause is governed by a purely epistatic interaction. Different scenarios are set up by varying the number of available single nucleotide polymorphisms (SNPs) in data, number of causative SNPs and ratio of case samples from two affected groups.

Detecting purely epistatic multi-locus interactions by an omnibus permutation test on ensembles of two-locus analyses.

Background: Purely epistatic multi-locus interactions cannot generally be detected via single-locus analysis in case-control studies of complex diseases. Recently, many two-locus and multi-locus analysis techniques have been shown to be promising for the epistasis detection. However, exhaustive multi-locus analysis requires prohibitively large computational efforts when problems involve large-scale or genome-wide data.