TITLE:
The Application of Cluster Analysis in Type II Diabetes Genome Association Study
AUTHORS:
Hankun Hu, Weidong Mao
KEYWORDS:
Genetic Disease, Genome Association Study, Cluster Algorithm
JOURNAL NAME:
Journal of Computer and Communications,
Vol.2 No.9,
July
11,
2014
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.