Con-AAE: contrastive cycle adversarial autoencoders for single-cell multi-omics alignment and integration.

ABSTRACT:

Motivation

We have entered the multi-omics era and can measure cells from different aspects. Hence, we can get a more comprehensive view by integrating or matching data from different spaces corresponding to the same object. However, it is particularly challenging in the single-cell multi-omics scenario because such data are very sparse with extremely high dimensions. Though some techniques can be used to measure scATAC-seq and scRNA-seq simultaneously, the data are usually highly noisy due to the limitations of the experimental environment.

Results

To promote single-cell multi-omics research, we overcome the above challenges, proposing a novel framework, contrastive cycle adversarial autoencoders, which can align and integrate single-cell RNA-seq data and single-cell ATAC-s

SUBMITTER: Wang X 

PROVIDER: S-EPMC10101696 | biostudies-literature | 2023 Apr

REPOSITORIES: biostudies-literature