Fig. 2: MOSA reconstruction of drug response and CRISPR-Cas9 datasets.
From: Synthetic augmentation of cancer cell line multi-omic datasets using unsupervised deep learning
a MOSA reconstruction quality measured using a 10-fold cross-validation. After reconstructing all test folds, they are concatenated and the reconstruction quality score is calculated as the Pearson’s r between the reconstructed and actual measured values. Features ranked by their reconstruction quality are shown for the drug response (left) and the CRISPR-Cas9 (right) datasets. Duplicated drug names represent replicated screens for the same drug. Representative examples of strongly selective CRISPR-Cas9 and drug responses are labeled. b MOSA’s partial dataset augmentation (missing value imputation) of drug IC50s compared to recent independent drug response screens. c–e, similar to b, using MOFA, MOVE and mean imputed values, respectively.
