A gene selection method for microarray data based on sampling

Authors:
Yungho Leu;Chien-Pang Lee;Hui-Yi Tsai
Affiliations:
Department of Information Management, National Taiwan University of Science and Technology, Taipei, Taiwan, ROC;Department of Information Management, National Taiwan University of Science and Technology, Taipei, Taiwan, ROC;Department of Information Management, National Taiwan University of Science and Technology, Taipei, Taiwan, ROC
Venue:
ICCCI'10 Proceedings of the Second international conference on Computational collective intelligence: technologies and applications - Volume Part II
Year:
2010

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Abstract

Microarray technology has become an important tool for biologists in recent years. It can obtain the expressions of a large amount of genes in a single experiment. One of the research issues of microarray is to select a set of relevant genes from a large number of genes to assist clinical diagnosis. In this paper, we propose a method for gene selection in microarray data. In the proposed method, we first classify genes into three different groups of genes according to their expressions in the microarray experiment. Then, we use probability sampling method to generate several candidate subsets of genes. Finally, we use χ2- test for homogeneity to select the relevant genes. The experiment results show that the proposed method is better than the other methods in terms of classification accuracy and the number of genes selected.