Identification of Ancestry Informative Markers from Chromosome-Wide Single Nucleotide Polymorphisms Using Symmetrical Uncertainty Ranking

Abstract

Ancestry informative markers (AIMs) have been proven to contain necessary information for population classification. In this article, round robin symmetrical uncertainty ranking for preliminary AIM screening is proposed. Each single nucleotide polymorphism (SNP) is assigned a rank based on its ability to separate two populations from each other. In a multi-population scenario, all possible population pairs are considered and the screened SNP set incorporates top-ranked SNPs from every pair-wise comparison. After the preliminary screening, SNPs are further screened by a wrapper which is embedded with a naive Bayes classifier. A classification model is subsequently constructed from the finally screened SNPs via a naive Bayes classifier. The application of the proposed procedure to the HapMap data indicates that AIM panels can be found on all chromosomes. Each panel consists of 11 to 24 SNPs and can be used to completely classify the CEU, CHB, JPT and YRI populations. Moreover, all panels are smaller than the AIM panels reported in previous studies.

A Feature Selection Application for Classification: A Banking Application

“…Bir değişken için simetrik belirsizlik değerinin yüksek olması, bu değişken ile hedef değişken arasında güçlü bir ilişkinin bulunduğunu gösterir ve bu değişkenin sınıflandırmada kullanılmasının faydalı olduğu anlamına gelir (Piroonratana et al 2010).…”