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Damian C. Melles, Raymond F.J. Gorkink, Hélène A.M. Boelens, Susan V. Snijders, Justine K. Peeters, Michael J. Moorhouse, Peter J. van der Spek, Willem B. van Leeuwen, Guus Simons, Henri A. Verbrugh, Alex van Belkum
Published in Volume 114, Issue 12
J Clin Invest. 2004; 114(12):1732–1740 doi:10.1172/JCI23083
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Figure 3

Cluster analysis of the 1,056 S. aureus strains using OmniViz. The cells in the correlation visualization are colored by Pearson’s correlation coefficient values with deeper colors indicating higher positive (red) or negative (blue) correlations. The scale bar (underneath the figure) indicates 100% correlation (red) toward 100% anticorrelation (blue). In order to reveal correlation patterns, a matrix-ordering method was applied to rearrange the samples. The OmniViz correlation view generated with 1,056 strains was adapted so that descriptive (clinical) parameters could be plotted directly adjacent to the original diagonal. The black and white bar on the left indicates the 5 AFLP groups based on PCA. This figure shows additional subclustering in major group I (a–j) as well as in minor group IVa, indicated by several lines. The dotted lines identify blocks of minimal changes in 1 cluster or subcluster. The corresponding MLST data (see also Figure 4) are shown on the right side of the figure. The distributions of the strains from different origins are visualized as red lines in the diagonal red and green bars of the figure (numbered 2–9). Variable 1 indicates the different AFLP clusters based on PCA; 2, carriage isolates, children (n = 400); 3, carriage isolates, elderly adults (n = 429); 4, invasive isolates, total (n = 164); 5, invasive isolates, children (n = 74); 6, invasive isolates, elderly adults (n = 90); 7, invasive isolates, children (deep-seated and soft-tissue infections) (n = 18); 8, impetigo isolates (n = 40); 9, MRSA (n = 21).