scCAN: Single-Cell Clustering using Autoencoder and Network Fusion

A single-cell Clustering method using 'Autoencoder' and Network fusion ('scCAN') 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: 1.0.1
Depends: R (≥ 3.4), scDHA, FNN
Imports: purrr, stats, markdown
Suggests: knitr
Published: 2021-07-19
Author: Bang Tran [aut, cre], Duc Tran [aut], Hung Nguyen [aut], Tin Nguyen [fnd]
Maintainer: Bang Tran <bang.t.s at nevada.unr.edu>
License: LGPL-2 | LGPL-2.1 | LGPL-3 [expanded from: LGPL]
NeedsCompilation: no
Materials: README
CRAN checks: scCAN results

Downloads:

Reference manual: scCAN.pdf
Vignettes: scCAN package manual
Package source: scCAN_1.0.1.tar.gz
Windows binaries: r-devel: scCAN_1.0.1.zip, r-release: scCAN_1.0.1.zip, r-oldrel: scCAN_1.0.1.zip
macOS binaries: r-release (arm64): scCAN_1.0.1.tgz, r-release (x86_64): scCAN_1.0.1.tgz, r-oldrel: scCAN_1.0.1.tgz
Old sources: scCAN archive

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