SciCAN: single-cell chromatin accessibility and gene expression data integration via cycle-consistent adversarial network.

ABSTRACT: The boom in single-cell technologies has brought a surge of high dimensional data that come from different sources and represent cellular systems from different views. With advances in these single-cell technologies, integrating single-cell data across modalities arises as a new computational challenge. Here, we present an adversarial approach, sciCAN, to integrate single-cell chromatin accessibility and gene expression data in an unsupervised manner. We benchmarked sciCAN with 5 existing methods in 5 scATAC-seq/scRNA-seq datasets, and we demonstrated that our method dealt with data integration with consistent performance across datasets and better balance of mutual transferring between modalities than the other 5 existing methods. We further applied sciCAN to 10X Multiome data and confirm

SUBMITTER: Xu Y 

PROVIDER: S-EPMC9464763 | biostudies-literature | 2022 Sep

REPOSITORIES: biostudies-literature