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  3. QuanTC: Inference and multiscale model of epithelial-to-mesenchymal transition via single-cell transcriptomic data

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QuanTC: Inference and multiscale model of epithelial-to-mesenchymal transition via single-cell transcriptomic data

What is being modeled?
Identifying cell fate transition from scRNA-seq data with applications to EMT
Description & purpose of resource

An unsupervised learning of single-cell transcriptomic data for identification of individual cells making transition between all cell states, and inference of genes that mark transitions.

Spatial scales
cellular
tissue
organ
Temporal scales
1 - 103 s
hours
days
This resource is currently
mature and useful in ongoing research
Has this resource been validated?
Yes
Link to Resource Credibility Assessment
QuanTC: Inference and multiscale model of epithelial-to-mesenchymal transition via single-cell transcriptomic data
Key publications (e.g. describing or using resource)

Sha, Yutong, Shuxiong Wang, Peijie Zhou, and Qing Nie. "Inference and multiscale model of epithelial-to-mesenchymal transition via single-cell transcriptomic data." Nucleic acids research 48, no. 17 (2020): 9505-9520.

DOI link to publication describing this resource

https://doi.org/10.1093/nar/gkaa725

Link to resource
QuanTC package
Collaborators
Qing Nie (PI)
PI contact information
qnie@uci.edu
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