Understanding the biologic significance of alternative splicing has been impeded by the difficulty in systematically identifying and validating transcript isoforms. Current exon array workflows suggest several different filtration steps to reduce the number of tests and increase the detection of alternative splicing events. In this study, we examine the effects of the suggested pre-analysis filtration by detection above background P value or signal intensity. This is followed post-analytically by restriction of exon expression to a fivefold change between groups, limiting the analysis to known alternative splicing events, or using the intersection of the results from different algorithms. Combinations of the filters are also examined. We find that none of the filtering methods reduces the number of technical false-positive calls identified by visual inspection. These include edge effects, nonresponsive probe sets, and inclusion of intronic and untranslated region probe sets into transcript annotations. Modules for filtering the exon microarray data on the basis of annotation features are needed. We propose new approaches to data filtration that would reduce the number of technical false-positives and therefore, impact the time spent performing visual inspection of the exon arrays.