Package: SCENT
Title: Single Cell Entropy for Estimating Differentiation Potency
Version: 2.0.0
Authors@R: c(
    person("Andrew E", "Teschendorff", email = "andrew@picb.ac.cn", role = "aut",
           comment = "Original algorithm"),
    person("Zaoqu", "Liu", email = "liuzaoqu@163.com", role = c("aut", "cre"),
           comment = c(ORCID = "0000-0002-0452-742X"))
    )
Author: Andrew E Teschendorff [aut], Zaoqu Liu [aut, cre]
Maintainer: Zaoqu Liu <liuzaoqu@163.com>
Description: Estimates differentiation potency of single cells from
        scRNA-Seq data using signaling entropy on protein interaction
        networks. Implements both the full Signaling Entropy Rate (SR)
        and the fast CCAT approximation. Based on the method described
        in Teschendorff AE, Enver T (2017) <doi:10.1038/ncomms15599>.
License: GPL-3
Encoding: UTF-8
LazyData: true
Roxygen: list(markdown = TRUE)
RoxygenNote: 7.3.3
Depends: R (>= 4.0.0)
Imports: Matrix, igraph, stats, Rcpp (>= 1.0.0)
LinkingTo: Rcpp, RcppArmadillo
Suggests: testthat (>= 3.0.0), knitr, rmarkdown, ggplot2, Seurat,
        dplyr, tidyr, viridis, pheatmap
VignetteBuilder: knitr
URL: https://github.com/Zaoqu-Liu/SCENT,
        https://zaoqu-liu.github.io/SCENT/
BugReports: https://github.com/Zaoqu-Liu/SCENT/issues
Config/pak/sysreqs: libglpk-dev libxml2-dev
Repository: https://zaoqu-liu.r-universe.dev
Date/Publication: 2026-01-23 09:38:34 UTC
RemoteUrl: https://github.com/Zaoqu-Liu/SCENT
RemoteRef: main
RemoteSha: 8a3a80953befa50b4320249d28e1ce0afb6c5e06
NeedsCompilation: yes
Packaged: 2026-06-22 09:55:23 UTC; root