This reformulation leverages advances in deep generative modeling20, which have become integral to many single-cell omics analytical tasks such as multimodal data integration21,22, perturbation modeling23,24 and
PROBABILISTIC generative modelsDATA integrationTECHNOLOGICAL innovationsREGULATOR genesFEATURE selectionRecent technological advancements in single-cell genomics have enabled joint profiling of gene expression and alternative modalities at unprecedented scale. Consequently, the complexity of multi-omics data sets is ...
Here, we introduce scCross. At its foundation, scCross excels in its function of single-cell multi-omics data integration, bringing unparalleled precision to the assimilation of diverse data modalities. While preserving its primary proficiency in this arena, the most distinctive feature of scCross ...
siVAE infers interpretable representations of single-cell genomic data.aThe input to siVAE is a cell-by-feature matrix; shown here is a synthetic gene expression matrix of eight genes, four of which are tightly regulated (genes 1–4), and the other four of which vary independently (genes 5...
Single-cell multimodal sequencing technologies are developed to simultaneously profile different modalities of data in the same cell. It provides a unique opportunity to jointly analyze multimodal data at the single-cell level for the identification of distinct cell types. A correct clustering result is...
Here, we present a new single-cell multiomics integration method based on variational PoE autoencoders, Single-cell Multiomics Autoencoder Integration (scMaui) to address the aforementioned limitations in VAE-based single-cell multiomics integration models (Fig.1). scMaui can model all possible ki...
3. Essential concepts in single-cell omics 4. Deep Learning applications in single-cell omics 5. Conclusions and future perspective Declarations CRediT authorship contribution statement Declaration of Competing Interest Acknowledgments Data availability ReferencesShow full outline Cited by (48) Figures (6...
Genome Biology (2024) 25:198 https://doi.org/10.1186/s13059-024-03338-z Genome Biology METHOD Open Access scCross: a deep generative model for unifying single‑cell multi‑omics with seamless integration, cross‑modal generation, and in silico exploration Xiuhui Yang1,2,3,...
Modifications, such as the β-VAE and other variations on it [27], have been developed to address these issues and adapted for single-cell analysis. In addition, depending on the value of β, these models also have been shown to improve the disentanglement, or the independence of the ...
With the development of single-cell technology, many cell traits can be measured. Furthermore, the multi-omics profiling technology could jointly measure two or more traits in a single cell simultaneously. In order to process the various data accumulated