Automated Pattern Ranking in Differential Display Data Analysis

Gene expression analysis by differential display (DD) is limited by the labor-intensive visual evaluation of the electrophoretic data traces. We describe a flexible method for computer-assisted ranking of expression patterns in data from DD experiments. The method is based on a pairwise alignment and comparison of the quantitative trace data with respect to specific expression patterns defined by the investigator. The observed patterns are ranked according to a score value that identifies the most potential findings to be confirmed visually instead of the vast amount of original results. This two-step approach, enabled by the efficient computer algorithm for gene expression pattern comparison, will increase the percentage of true-positive findings chosen for the tedious downstream processing, while minimizing the cost and labor involved in large scale DD data analysis.