Fig. 1
From: Clust: automatic extraction of optimal co-expressed gene clusters from gene expression data
Expectations and outcomes for application of data-partitioning methods to co-expression clustering. a, b Simulated gene expression data for 500 genes with increasing noise (D1–D4) (Additional file 1: Table S1). a All genes. b Profiles of the genes in each of the three simulated clusters as well as the extra unclustered genes at each one of the four levels of dispersion. The horizontal axis of each plot represents the six different time-points, while the vertical axis represents gene expression values. c The results of applying a partitioning method (k-means in this case) to the same simulated datasets. d Heat-maps that show the percentage of genes in a cluster that also fit well within each one of the other clusters