The hardware and bandwidth for this mirror is donated by METANET, the Webhosting and Full Service-Cloud Provider.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]metanet.ch.

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 csus.edu>
License: LGPL-2 | LGPL-2.1 | LGPL-3 [expanded from: LGPL]
NeedsCompilation: no
Materials: README
CRAN checks: scCAN results

Documentation:

Reference manual: scCAN.pdf
Vignettes: scCAN

Downloads:

Package source: scCAN_1.0.5.tar.gz
Windows binaries: r-devel: scCAN_1.0.5.zip, r-release: scCAN_1.0.5.zip, r-oldrel: scCAN_1.0.5.zip
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

Linking:

Please use the canonical form https://CRAN.R-project.org/package=scCAN to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.