Figure 5

Discovering gene expression profiles with consensus clustering. A fruitfly PNS gene expression data set (TIS, APJ, data available from the gene expression omnibus (GEO) accession GSE21520) was used to test the ability of clusterCons to identify gene expression profiles across a developmental time-series. (A) Consensus clustering was performed with agnes, pam and k-means algorithms with 100 iterations and cluster numbers k = {2, 3...10}. The optimal cluster number was estimated by calculating first the AUC and then the delta-K values for the consensus and merge consensus matrices and a delta-K plot generated. The small, but consistent peak at k = 6 for k-means, pam and merge consensus matrices was select for further study using the k-means clustering structure. (B) Relative gene expression means were plotted for all probe-sets by cluster revealing discrete and stereotypical profiles describing stage and genotype specific features. Among these are profiles for early (clusters 2 and 4), mid (cluster 5) and late (clusters 1,3 and 6) expressed genes as well as differentiation of genes that are expressed lower (clusters 2 and 5) or higher (cluster 4) in the atonal mutant.