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- Title
sciCAN: single-cell chromatin accessibility and gene expression data integration via cycle-consistent adversarial network.
- Authors
Xu, Yang; Begoli, Edmon; McCord, Rachel Patton
- 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.
- Subjects
DATA integration; GENE expression; CHROMATIN; RNA sequencing; GENE regulatory networks
- Publication
NPJ Systems Biology & Applications, 2022, Vol 8, Issue 1, p1
- ISSN
2056-7189
- Publication type
Article
- DOI
10.1038/s41540-022-00245-6