Predicting drug polypharmacology from cell morphology readouts using variational autoencoder latent space arithmetic
Fig 4
Mean L2 distance (lower is better) between real and predicted profiles annotated with known polypharmacology (“A ∩ B”) mechanisms of action (MOAs) for three different VAE architectures, PCA, and original input space.
We show results for real and shuffled data across the two LINCS datasets. To enable a more meaningful and interpretable view, we zero-one normalized the L2 distances for each dataset. Each dot represents the mean L2 distance (values are normalized within each dataset) when LSA is performed using a specific model on a specific dataset.