ScME: a dual-modality factor model for single-cell multiomics embedding.

ABSTRACT:

Motivation

Single-cell multiomics technologies are emerging to characterize different molecular features of cells. This gives rise to an issue of combining various kinds of molecular features to dissect cell heterogeneity. Most single-cell multiomics integration methods focus on shared information among modalities while complementary information specific to each modality is often discarded.

Results

To disentangle and combine shared and complementary information across modalities, we develop a dual-modality factor model named scME by using deep factor modeling. Our results demonstrate that scME can generate a better joint representation of multiple modalities than those generated by other single-cell multiomics integration algorithms, which gives a clear elucidation of nuance

SUBMITTER: Zhou B 

PROVIDER: S-EPMC10234764 | biostudies-literature | 2023 Jun

REPOSITORIES: biostudies-literature