title	author	date	package	output
A brief tutorial for estimating differentiation potency of single cells using SCENT and CCAT	name affiliation Andrew E. Teschendorff CAS Key Lab of Computational Biology, PICB, SINH UCL Cancer Institute, University College London	2020-10-26	SCENT	BiocStyle::html_document toc_float true

Summary

The main purpose of the SCENT package is to provide a means of estimating the differentiation potency of single cells without the need to assume prior biological knowledge such as marker expression or timepoint. This may be particularly important in scenarios where a high dropout rate may preclude the use of a marker gene, in snapshot scRNA-Seq datasets of complex tissues where differentiation hierarchies are not well-established, or in cancer tissue where one may want to identify putative cancer stem-cell phenotypes.

Installation

To install:

library(devtools)
devtools::install_github("aet21/SCENT")

References

Teschendorff AE, Enver T. Single-cell entropy for accurate estimation of differentiation potency from a cell's transcriptome. Nat Commun. 2017 Jun 1;8:15599. doi: 10.1038/ncomms15599