Identification of differentially expressed genes for diabetes with parental history vs healthy using Microarray data analysis

Both environmental and genetic factors have roles in the development of any disease. A genetic disorder in a disease is caused by abnormalities in an individual´s genetic material (genome). The quest for an understanding of how genetic factors contribute to human disease is gathering speed. Differential gene expression analysis plays an important role for the study of genetic factors causing diseases. We proposed a method for identifying differentially expressed genes causing Type-2 diabetes mellitus using micro array data for diabetes with parental history and healthy. This method focuses on identifying multivariate and univariate outliers using Mahalanobis Distance, Minimum Co-variance Determinant (MCD) and other statistical methods. This method is applied on microarray data from two samples one from diabetes with parental history and the other from healthy and identified 1579 genes which are differentially expressed. Prior to analysis, the micro array data is normalized using Loess Normalization method.