Author(s)

Saeed Masoum^*, Ebrahim Haghir Ebrahimabadi

Department of Analytical Chemistry, Faculty of Chemistry, University of Kashan, Kashan, Iran.

DNA microarray is an authoritative method for investigation in various cancer and tumors such as renal cancer. Gene expression data include a huge amount of data that the selection of informative data among it is very difficult. Broadly chemometric methods have been used for statistical analysis of gene expression data and different algorithms are used for gene selection. Weighted voting algorithm (WVA) provides a statistical basis for the selection from an original 15,923 probesets, a limited number of most effective genes in discriminating two types of rats treated with Aristolochic acid (AA) and Ochratoxin A (OTA) drugs, that are two chemical compounds with specially toxic effect for kidney and cause renal cancer. In the next step, diminished microarray data are classified by partial least square discriminant analysis (PLSDA) and support vector machine (SVM) methods. Results show that these methods are efficient and sufficient for classification purpose.

DNA Microarray, Gene Selection, Renal Cancer, Weighted Voting Algorithm, Partial Least Square Discriminant Analysis

Masoum, S. and Ebrahimabadi, E. (2014) Weighted Voting Analysis of DNA Microarray for Gene Selection and Gene Expression Analysis of Two Types of Rats Treated with Aristolochic Acid and Ochratoxin A Drugs. Open Access Library Journal, 1, 1-12. doi: 10.4236/oalib.1100859.