Classification of Cattle Coat Color Based on Genotype Using Pattern Recognition Methods

Abstract

Several current research projects are focused on the creation of haplotype maps to identify and describe common genetic variation in some species. Studies on haplotype maps are key in understanding how natural selection has produced genomic differences between subspecies of a given species. Important insight can be obtained by determining which variations in the genotype are associated with important phenotypical differences between individuals. Pattern recognition theory and machine learning techniques are useful tools to reveal this connection from a large amount of data provided by haplotype maps. In this work, we applied discrete classifiers and feature selection techniques for the prediction of cattle coat color from genotypes. We compared the performance of different classification rules and showed the feasibility of this approach for the prediction of phenotype based on genotype.