A Multi-population chi2 Test Approach to Informative Gene Selection

This paper proposes a multi-population χ test method for informative gene selection of a tumor from microarray data based on the statistical multi-population χ test with the sample data being grouped evenly. To test the effectiveness of the multi-population χ 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 χ test method can reach an optimum accuracy level of 100% on both colon and leukemia data sets.