Gene selection with multiple ordering criteria

Background: A microarray study may select different differentially expressed gene sets because of different selection criteria. For example, the fold-change and p-value are two commonly known criteria to select differentially expressed genes under two experimental conditions. These two selection criteria often result in incompatible selected gene sets. Also, in a two-factor, say, treatment by time experiment, the investigator may be interested in one gene list that responds to both treatment and time effects. Results: We propose three layer ranking algorithms, point-admissible, line-admissible (convex), and Pareto, to provide a preference gene list from multiple gene lists generated by different ranking criteria. Using the public colon data as an example, the layer ranking algorithms are applied to the three univariate ranking criteria, fold-change, p-value, and frequency of selections by the SVM-RFE classifier. A simulation experiment shows that for experiments with small or moderate...

• Type: Journal
• Year: 2007
• Where: BMCBI
• Authors: James J. Chen, Chen-An Tsai, ShengLi Tzeng, Chun-Houh Chen
• Keywords: BMCBI 2007, Layer Ranking, Layer Ranking Algorithms, Ranking