The training data from the 'all cells' data split was used to train all models. In the case of autoencoders, the validation set was used for early stopping, providing additional regularisation. After training, the test set was used to produce the 2D projections that will be discussed in the results section. Visualising projections on the test set, instead of the whole dataset, provides additional reassurance that any patterns that emerge are not the result of overfitting to the training data. It should be clarified, however, that it does not in itself guarantee that the autoencoders have not simply learned the identity function. The aforementioned denoising strategy is what ameliorated this problem.