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. 2004 Mar 1;113(5):709–717. doi: 10.1172/JCI19850

Figure 5.

Figure 5

PCA analysis and 2D hierarchical clustering of virtual two-dye experiments. (A) PCA projection showing that the overall analyzed data set is organized in two large clusters on the first two principal components. The two clusters discriminate genes on the expression differences existing between wk22nt mice and the other two groups. In both clusters, wk10nt and wk22pb are grouped together and they are separated from wk22nt. (B) PCA projection showing that the third principal component does not contribute at all to the data clustering. (C) Profiles of PCA cluster 1: 1,122 probe sets upmodulated in wk22pb/wk10nt with respect to wk22nt; clusters a–e represent the probe sets upmodulated only in wk22pb. (D) Profiles of PCA cluster 2: 1,057 probe sets downmodulated in wk22pb/wk10nt with respect to wk22nt.