sciCAN: single-cell chromatin accessibility and gene expression data integration via cycle-consistent adversarial network.
NPJ Syst Biol Appl
; 8(1): 33, 2022 09 12.
Article
in En
| MEDLINE
| ID: mdl-36089620
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 confirmed that the integrated representation preserves biological relationships within the hematopoietic hierarchy. Finally, we investigated CRISPR-perturbed single-cell K562 ATAC-seq and RNA-seq data to identify cells with related responses to different perturbations in these different modalities.
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Main subject:
Chromatin
/
Single-Cell Analysis
Language:
En
Journal:
NPJ Syst Biol Appl
Year:
2022
Document type:
Article
Affiliation country:
United States
Publication country:
ENGLAND
/
ESCOCIA
/
GB
/
GREAT BRITAIN
/
INGLATERRA
/
REINO UNIDO
/
SCOTLAND
/
UK
/
UNITED KINGDOM