Methods for simultaneously identifying coherent local clusters with smooth global patterns in gene expression profiles

摘要

BackgroundThe hierarchical clustering tree (HCT) with a dendrogram [] and the singular value decomposition (SVD) with a dimension-reduced representative map [] are popular methods for two-way sorting the gene-by-array matrix map employed in gene expression profiling. While HCT dendrograms tend to optimize local coherent clustering patterns, SVD leading eigenvectors usually identify better global grouping and transitional structures.