Guided co-clustering transfer across unpaired and paired single-cell multi-omics data.

ABSTRACT:

Motivation

Single-cell multi-omics technologies enable the simultaneous profiling of gene expression and chromatin accessibility, providing complementary insights into cellular identity and gene regulatory mechanisms. However, integrating paired scRNA-seq and scATAC-seq data (i.e. profiles from the same single cell) remains challenging due to inherent sparsity, technical noise, and the limited availability of high-quality paired measurements. In contrast, large-scale unpaired scRNA-seq datasets often exhibit robust and biologically meaningful cell cluster structures.

Results

We introduce Guided Co-clustering Transfer (GuidedCoC), a novel framework that transfers structural knowledge from unpaired scRNA-seq source data to improve both cell clustering and feature alignment in

SUBMITTER: Li H 

PROVIDER: S-EPMC12696646 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature