Hierarchic clustering analyses of gene expression profiles in APL models either with or without retinoid treatment. For hierarchic clustering analysis, GeneChip software-generated data sets were entered as 18 independent experiments (6 experimental groups in triplicate) into GeneSpring software, and Experiment Normalization was used to standardize the microarray data. Following standardization, data sets were subjected to a Statistical Group Comparison Filter in order to test for significant differences in expression levels between experimental groups. A nonparametric (Kruskal-Wallis) test with a P value cutoff of .001 was applied to generate a list of genes that can best differentiate various experimental groups. Gene and experiment trees were generated using this gene list; similarities are measured by Spearman correlation (separation ratio 0.5; minimum distance 0.001). The color in each cell of the cluster reflects the mean-centered expression level of the gene. The color scale bar reflects normalized expression levels (0 to 6.0). Red and blue colors denote gene expression levels that are either higher or lower than the mean expression level, respectively.