DeepCCI: a deep learning framework for identifying cell-cell interactions from single-cell RNA sequencing data

Jiang, Q.; Yang, W.; Xu, Z.; Luo, M.; Cai, Y.; Xu, C.; Wang, P.; Wei, S.; Xue, G.; Jing, X.; Cheng, R.; Que, J.; Zhou, W.; Pang, F.; Nie, H.

doi:10.1101/2022.11.11.516061

bioRxiv · 10.1101/2022.11.11.516061

DeepCCI: a deep learning framework for identifying cell-cell interactions from single-cell RNA sequencing data

Jiang, Q.·Yang, W.·Xu, Z.·Luo, M.·Cai, Y.·Xu, C.·Wang, P.·Wei, S.·Xue, G.·Jing, X.·Cheng, R.·Que, J.·Zhou, W.·Pang, F.·Nie, H.

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Abstract

With the rapid development of high throughput single-cell RNA sequencing (scRNA-seq) technologies, it is of high importance to identify Cell-cell interactions (CCIs) from the ever-increasing scRNA-seq data. However, limited by the algorithmic constraints, current computational methods based on statistical strategies ignore some key latent information contained in scRNA-seq data with high sparsity and heterogeneity. To address the issue, here, we developed a deep learning framework named DeepCCI to identify meaningful CCIs from scRNA-seq data. Applications of DeepCCI to a wide range of publicly available datasets from diverse technologies and platforms demonstrate its ability to predict significant CCIs accurately and effectively.

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Jiang, Q., Yang, W., Xu, Z., Luo, M., Cai, Y., Xu, C., Wang, P., Wei, S., Xue, G., Jing, X., Cheng, R., Que, J., Zhou, W., Pang, F., Nie, H.. 2022-11-13. DeepCCI: a deep learning framework for identifying cell-cell interactions from single-cell RNA sequencing data. https://doi.org/10.1101/2022.11.11.516061

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