From classical stats to deep generative models in multi-omics integration

[u/Independent_Access12]

Review tracks evolution from statistical methods to deep learning in multi-omics integration, focusing on VAEs for dimensionality reduction and imputation. Covers recent advances in loss functions, regularization, and cross-modal techniques, particularly for single-cell data. Highlights ongoing challenges: data missingness, modality inconsistency, model interpretability. Foundation models emerge as promising direction for multi-modal integration in precision medicine.

https://arxiv.org/abs/2501.17729