sciCAN: Single-cell chromatin accessibility and gene expression data integration via Cycle-consistent Adversarial Network

Xu, Y.; Begoli, E.; McCord, R. P.

doi:10.1101/2021.11.30.470677

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bioRxiv · 10.1101/2021.11.30.470677

sciCAN: Single-cell chromatin accessibility and gene expression data integration via Cycle-consistent Adversarial Network

Xu, Y.·Begoli, E.·McCord, R. P.

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Abstract

The booming single-cell technologies bring a surge of high dimensional data that come from different sources and represent cellular systems from different views. With advances in single-cell technologies, integrating single-cell data across modalities arises as a new computational challenge and gains more and more attention within the community. Here, we present a novel adversarial approach, sciCAN, to integrate single-cell chromatin accessibility and gene expression data in an unsupervised manner. We benchmarked sciCAN with 3 state-of-the-art (SOTA) methods in 5 scATAC-seq/scRNA-seq datasets, and we demonstrated that our method dealt with data integration with better balance of mutual transferring between modalities than the other 3 SOTA methods. We further applied sciCAN to 10X Multiome data and confirmed the integrated representation preserves information of the hematopoietic hierarchy. Finally, we investigated CRSIPR-perturbed single-cell K562 ATAC-seq and RNA-seq data to identify cells with related responses to different perturbations in these different modalities.

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Xu, Y., Begoli, E., McCord, R. P.. 2021-12-01. sciCAN: Single-cell chromatin accessibility and gene expression data integration via Cycle-consistent Adversarial Network. https://doi.org/10.1101/2021.11.30.470677

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