Figure 5.

Comparison of alignment scores for (A) sponge data, (B) AD data and (C) HFHS data before and after batch effect correction using different methods. A large alignment score indicates that samples from different batches are well mixed based on the PCA dissimilarity matrix. The alignment scores between methods can only be compared when samples have similar sample distribution in their PCA projection, i.e. for sponge and HFHS data. In these two case studies, our method PLSDA-batch had a better performance than the univariate methods ComBat and removeBatchEffect.