scCAN: Single-Cell Clustering using Autoencoder and Network Fusion

A single-cell Clustering method using 'Autoencoder' and Network fusion ('scCAN') Bang Tran (2022) <doi:10.1038/s41598-022-14218-6> for segregating the cells from the high-dimensional 'scRNA-Seq' data. The software automatically determines the optimal number of clusters and then partitions the cells in a way such that the results are robust to noise and dropouts. 'scCAN' is fast and it supports Windows, Linux, and Mac OS.

Version: 1.0.5
Depends: R (≥ 4.2.0), scDHA, FNN, purrr
Imports: stats
Suggests: knitr, rmarkdown
Published: 2024-06-13
DOI: 10.32614/CRAN.package.scCAN
Author: Bang Tran [aut, cre], Duc Tran [aut], Hung Nguyen [aut], Tin Nguyen [fnd]
Maintainer: Bang Tran <s.tran at>
License: LGPL-2 | LGPL-2.1 | LGPL-3 [expanded from: LGPL]
NeedsCompilation: no
Materials: README
CRAN checks: scCAN results


Reference manual: scCAN.pdf
Vignettes: scCAN


Package source: scCAN_1.0.5.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): scCAN_1.0.5.tgz, r-oldrel (arm64): scCAN_1.0.5.tgz, r-release (x86_64): scCAN_1.0.5.tgz, r-oldrel (x86_64): scCAN_1.0.5.tgz
Old sources: scCAN archive


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