Fig. 2
From: Survival marker genes of colorectal cancer derived from consistent transcriptomic profiling
Plots presenting the distribution of the 1273 samples from 7 datasets (GSEs) obtained by Principal Component Analysis (PCA) of the global gene expression profile of each sample; that converts the signal of each sample using an orthogonal transformation in linearly uncorrelated variables called principal components or dimensions. Each plot presents the values of the two main dimensions (dim 1 versus dim 2) and corresponds to the PCA results obtained using the expression data calculated with different preprocessing and normalization methods. The methods applied were: a RMA; b RMA plus ComBat; c fRMA; d fRMA plus ComBat; e fRMA plus scaling of the data using mean-centered expression values. The samples of each batch are identified by color dots following the colors legend