Figure 2. Adjustment for non-biological experimental variation.
Multidimensional scaling of the combined training set revealed that, before application of the batch adjustment algorithm, each dataset clearly separated from all the others (“batch effect”), whereas after correction of batch effect, samples from all datasets were well intermixed.