Small ancestry informative marker panels for complete classification between the original four HapMap populations

TL;DR

This paper presents a new protocol for identifying small sets of ancestry informative markers (AIMs) from genome data, enabling complete classification of four HapMap populations with significantly fewer SNPs than previous methods.

Contribution

The study introduces a novel three-step protocol combining selection and classification techniques to identify minimal AIM panels for population classification.

Findings

Identified 10 and 16 SNP panels for complete classification of four populations.

Panels are at least four times smaller than previous AIM panels.

The protocol is potentially applicable to larger sets of populations.

Abstract

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: (a) identification of potential positive selection regions via Fst extremity measurement, (b) SNP screening via two-stage attribute selection and (c) classification model construction using a naive Bayes classifier. The two-stage attribute selection is composed of a newly developed round robin symmetrical uncertainty ranking technique and a wrapper embedded with a naive Bayes classifier. The protocol has been applied to the HapMap Phase II data. Two AIM panels, which consist of 10 and 16 SNPs that lead to complete classification between CEU, CHB, JPT and YRI populations, are identified. Moreover, the panels are at least four times smaller than those reported in previous studies. The results suggest that the protocol could be useful in a scenario involving a larger number of populations.