TITLE:
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
AUTHORS:
Saeed Masoum, Ebrahim Haghir Ebrahimabadi
KEYWORDS:
DNA Microarray, Gene Selection, Renal Cancer, Weighted Voting Algorithm, Partial Least Square Discriminant Analysis
JOURNAL NAME:
Open Access Library Journal,
Vol.1 No.6,
September
23,
2014
ABSTRACT: 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.