DIMM-SC
DIMMSC is an R package for clustering droplet-based single cell transcriptomic data. It uses Dirichlet mixture prior to characterize variations across different clusters. An expectation-maximization algorithm is used for parameter inference. This package can provide clustering uncertainty.
Reference
Zhe Sun, Ting Wang, Ke Deng, Xiao-Feng Wang, Robert Lafyatis, Ying Ding, Ming Hu, Wei Chen. DIMM-SC: A Dirichlet mixture model for clustering droplet-based single cell transcriptomic data. Bioinformatics 2017.
Contact
Please feel free to contact us when you have questions.
Wei Chen ( wei.chen@chp.edu) or Ming Hu ( hum@ccf.org)
To homepage: Wei Chen
Last update: Aug 2017