An Efficient Distributed SNP Selection Method for Porcine Breed Classification

Abstract

In principle, a porcine Single Nucleotide Polymorphism (SNP—a specific piece of nucleotide in a DNA sequence) can be associated with a trait of an individual pig, like its meat quality or resistance to common diseases. It is most desirable to obtain a smallest number of most significant SNPs in genomic research and several computer classification algorithms have been used to find a small number of SNPs. This study proposed a vertically distributed feature selection method incorporating a modified binary flower pollination and a support vector machine classifier for selecting significant porcine SNPs. The proposed method was evaluated and compared against four baseline methods. It provided a mean number of 128.4 selected SNPs that resulted in 94.57% classification accuracy.