OmiDos

Integrating single-cell multi-omics data is crucial for understanding the complex regulatory mechanisms governing cellular functions. However, a significant challenge arises from the concurrent existence of shared mechanisms across diverse cellular states and condition-specific features, particularly within dynamic and heterogeneous microenvironments. Most existing integration approaches struggle to effectively distinguish between shared and modality-specific features, leading to misinterpretation of regulatory dynamics. Here, we introduce OmiDos, a novel dynamic orthogonal deep generative model, specifically designed to disentangle shared and unique molecular signatures across multi-omics layers in single-cell multi-omics data. Unlike prior methods that rely on simplistic assumptions about shared features, OmiDos leverages deep transfer learning to extract invariant shared signals from paired data while enforcing orthogonality constraints to separate modality-specific signals into distinct latent spaces. To address unpaired data, OmiDos incorporates an adversarial discriminator combined with noise contrastive estimation. Furthermore, OmiDos features a decoder layer enhanced by a maximum mean discrepancy regularization, enabling robust batch correction across diverse experimental conditions. We benchmark OmiDos against a wide range of multi-omics datasets, demonstrating superior accuracy and robustness in integrating complex, high-dimensional data. In a mouse secondary palate development dataset, OmiDos precisely identified a critical enhancer at the genomic locus chr16: 32697085-32697585, elucidating its essential role in regulating \emph{Muc4} expression. Its activity strongly correlates with the regulatory dynamics observed in E13.5 and E14.5 epithelial cell differentiation and migration. When applied to a medulloblastoma dataset, OmiDos revealed a dynamic regulatory transition, characterized by a shift from predominant reliance on distal regulatory elements during early developmental stages to a marked preference for proximal regulatory elements in advanced tumor stages.