Clustering, leaf-ordering and visualization for intuitive analysis of deoxyribonucleic-acid chip data

Abstract

Generally the result data from DNA chip experiments have lots of gene expression information. Scientists want to get perspective insight or want to find intuitive fact from that data. Hierarchical clustering is the most widely used method for analysis of gene expression data. In this paper, we address leaf-ordering, which is a post-processing for the dendrograms - a sort of edge-weighted binary trees - created by hierarchical clustering and we present a new approach for leaf-ordering scheme. And we show the comparison results for our approach and the existing approach.