A multi-population χ2 test approach to informative gene selection

Abstract

This paper proposes a multi-population χ2 test method for informative gene selection of a tumor from microarray data based on the statistical multi-population χ2 test with the sample data being grouped evenly. To test the effectiveness of the multi-population χ2 test method, we use the support vector machine (SVM) to construct a tumor diagnosis system (i.e., a binary classifier) based on the identified informative genes on the colon and leukemia data. It is shown by the experiments that the constructed diagnosis system with the multi-population χ2 test method can 100% correctness rate of diagnosis on colon dataset and 97.1% correctness rate of diagnosis on leukemia dataset, respectively. © Springer-Verlag Berlin Heidelberg 2005.