It is well known that disease of human and economic traits of livestock are affected a lot by gene combination effect rather than a single gene effect. But existing methods have disadvantages such as heavy computing, many expenses and long time. In order to overcome those drawbacks, SNPHarvester was developed to find the main gene combinations among the many genes. In this paper, we used the superior gene combination which are related to the quality of the Korean beef cattle among sets of SNPs by SNPHarvester, and identified the superior genotypes using radial graph which can enhance various qualities of Korean beef among selected SNP combinations.

It is known that human disease and the economic traits of livestock are significantly affected by a gene combination effect rather than a single gene effect. Existing methods to study this gene combination effect have disadvantages such as heavy computing, cost and time; therefore, to overcome those drawbacks, the SNPHarvester was developed to find the main gene combinations. In this paper, we looked for gene combinations using an adjusted linear regression model. This research finds that superior gene combinations which are related to the quality of the Korean beef cattle among sets of SNPs using SNPHarvester. We also identify the superior genotypes using a decision tree that can enhance the various qualities of Korean beef among selected a SNP combination.

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