The Application of Cluster Analysis in Type II Diabetes Genome Association Study

Hankun Hu, Weidong Mao

Department of Pharmacy, Zhongnan Hospital, Wuhan University, Wuhan, China.
School of Science & Technology, Georgia Gwinnett College, Lawrenceville, USA.

DOI: 10.4236/jcc.2014.29001                

Abstract

Genetic diseases, such as Type II diabetes, are caused by a combination of environmental factors and mutations in multiple genes. Patients who have been diagnosed with such diseases cannot easily be treated. However, many diseases can be avoided if people at high risk change their living style, one example is their diet. Genome association study has been used to identify the risk factor of genetic disease. With the development of DNA microarray technique, it is possible to access the human genetic information related to specific diseases. This paper uses a combinatorial method to analyze the genetic case-control data for Type II diabetes. A distance based cluster method has been applied to publicly available genotype data on Type II diabetes for epidemiological study and achieved a high accurate result.

Keywords

Genetic Disease, Genome Association Study, Cluster Algorithm

Conflicts of Interest

The authors declare no conflicts of interest.

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