We conduct a comparative study of several statistical approaches on our own breast cancer Affymetrix microarray datasets. The strategy is designed primarily as a filter to select subsets of genes relevant for classification. We outline a general framework based on different statistical algorithms for determining a high-performing multigene predictor of response to the preoperative treatment of patients. We hope that our approach will provide straightforward and useful practical guidance for identification of genes, which can discriminate between biologically relevant classes in microarray datasets.