ScAWMV: an adaptively weighted multi-view learning framework for the integrative analysis of parallel scRNA-seq and scATAC-seq data.

ABSTRACT:

Motivation

Technological advances have enabled us to profile single-cell multi-omics data from the same cells, providing us with an unprecedented opportunity to understand the cellular phenotype and links to its genotype. The available protocols and multi-omics datasets [including parallel single-cell RNA sequencing (scRNA-seq) and single-cell ATAC sequencing (scATAC-seq) data profiled from the same cell] are growing increasingly. However, such data are highly sparse and tend to have high level of noise, making data analysis challenging. The methods that integrate the multi-omics data can potentially improve the capacity of revealing the cellular heterogeneity.

Results

We propose an adaptively weighted multi-view learning (scAWMV) method for the integrative analysis of paral

SUBMITTER: Zeng P 

PROVIDER: S-EPMC9805575 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature