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  3. scEpath: energy landscape-based inference of transition probabilities and cellular trajectories from single-cell transcriptomic data

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scEpath: energy landscape-based inference of transition probabilities and cellular trajectories from single-cell transcriptomic data

What is being modeled?
Cellular trajectories, transition probabilities, energy landscape.
Description & purpose of resource

scEpath is an approach that calculates energy landscapes and probabilistic directed graphs in order to reconstruct developmental trajectories.

Spatial scales
molecular
cellular
Temporal scales
1 - 103 s
hours
days
weeks to months
This resource is currently
mature and useful in ongoing research
Has this resource been validated?
Yes
Link to Resource Credibility Assessment
scEpath: energy landscape-based inference of transition probabilities and cellular trajectories from single-cell transcriptomic data
Can this resource be associated with other resources? (e.g.: modular models, linked tools and platforms)
Yes
Key publications (e.g. describing or using resource)

Suoqin Jin, Adam L. MacLean, Tao Peng, Qing Nie. scEpath: energy landscape-based inference of transition probabilities and cellular trajectories from single-cell transcriptomic data. Bioinformatics. 2018 Jun 15;34(12):2077-2086. doi: 10.1093/bioinformatics/bty058.

DOI link to publication describing this resource

10.1093/bioinformatics/bty058

Link to resource
scEpath package
Collaborators
Qing Nie
PI contact information
qnie@uci.edu
Related Documents
RELATED DOCUMENTS_scEpath.pptx1.07 MB
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