Fig. 1: Cancer multi-omics integration with MOSA.
From: Synthetic augmentation of cancer cell line multi-omic datasets using unsupervised deep learning
a Cancer cell line multi-omic datasets across the 1523 cancer cell lines. Purple represents measured screens, while orange represents gaps, i.e., missing screens, which were synthetically generated with MOSA. b Schematic of the autoencoder, MOSA, where encoders are represented at the top and decoders at the bottom. For simplicity, the integration of only two datasets is represented. Highlighted designs of MOSA are illustrated on the right. Created in BioRender. Cai, Z. (2023) BioRender.com/m96b457. c Dimensionality reduction visualized using Uniform Manifold Approximation and Projection (UMAP) representation of the trained MOSA joint latent space, where each dot represents a cancer cell line colored according to its tissue of origin.
