Abstract: A method and system for evaluating the quality of normalizing feature sets used in normalizing two or more data sets obtained from microarrays, and for iteratively normalizing two or more data sets. In a described implementation, a rank-consistency threshold employed in selection and/or refinement of invariant features from the one or more data sets varied, as needed, during each iteration of an iterative normalization method, so that the iterative normalization converges on a set of invariant features for which a metric ? falls below a threshold value. The metric ? may be calculated as the percentage of selected invariant features, or normalizing features, that are differentially expressed in one or more data sets, to a specified level of significance. For a perfect set of invariant, or normalizing, features, the metric ? has the value of 0. ?-metric values of increasing magnitude correspond to normalizing feature sets of decreasing utility for normalization.