Feature Selection in HexaMplot to Assess Drug Effect in cDNA Microarray Experiments

Three-color cDNA microarray experiments are designed to assess drug effects on a genomic scale in an original way. With this kind of expression data, we propose an effective algorithm, named HoughFeature, to extract the significant features of polymorphic gene expressions to quantify drug effects in hexaMplots. The Hough technique is used in our algorithm to detect the featured lines in hexaMplots corresponding to the diverse levels of drug effects on differentially expressed genes. Thus, based on hexaMplots, the side and therapeutic effects of drugs can be quantified with our methodology. We apply the framework to the experimental microarray data to assess the complex effect of PW-1 (an extract of Chinese medicine) on TCDD toxified HepG2 cells in detail. Such a methodology may be useful in forefront gene therapy to predict disease susceptibility, implement drug therapy, and assess their effects.