JSNMFuP: a unsupervised method for the integrative analysis of single-cell multi-omics data based on non-negative matrix factorization.

ABSTRACT: With the rapid advancement of sequencing technology, the increasing availability of single-cell multi-omics data from the same cells has provided us with unprecedented opportunities to understand the cellular phenotypes. Integrating multi-omics data has the potential to enhance the ability to reveal cellular heterogeneity. However, data integration analysis is extremely challenging due to the different characteristics and noise levels of different molecular modalities in single-cell data. In this paper, an unsupervised integration method (JSNMFuP) based on non-negative matrix factorization is proposed. This method integrates the information extracted from the latent variables of each omic through a consensus graph. High-dimensional geometrical structure is captured in the original data and

SUBMITTER: Zhang B 

PROVIDER: S-EPMC11924690 | biostudies-literature | 2025 Mar

REPOSITORIES: biostudies-literature