Fig. 1From: Combining location-and-scale batch effect adjustment with data cleaning by latent factor adjustmentVisualization of batch effect adjustment. First two principal components out of PCA performed on the covariate matrix of a microarray dataset studying alcoholism: raw, after batch effect adjustment according to ComBat, SVA using three factors and FAbatch using three factors. The first batch is depicted in bold and the numbers distinguish the two classes “alcoholic” (2) vs. “healthy control” (1). The contour lines represent batch-wise two-dimensional kernel estimates and the diamonds represent the batch-wise centers of gravities of the pointsBack to article page