Hierarchical clustering. Left: Hierarchical clustering of the 15 genes from the BioVis 2011 contest dataset  using the UPGMA method and the Euclidean distance as distance measure (left). Genes are partitioned into two large clusters, namely differentially expressed genes and genes showing no differential expression between affected and unaffected patients. Right: Aggregated visualization in iHAT showing 29 significant SNPs associated with the patients disease states. Patients have been aggregated into the two groups affected (red) and unaffected (white), genes have been aggregated according to the clustering.
Heinrich et al. BMC Bioinformatics 2012 13(Suppl 8):S2 doi:10.1186/1471-2105-13-S8-S2