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: |
1.0.6 |
| Depends: |
R (≥ 4.2.0), scDHA (≥ 1.2.0), FNN, purrr |
| Imports: |
stats, parallel |
| Suggests: |
knitr, rmarkdown |
| Published: |
2026-11-04 |
| 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> |
| BugReports: |
https://github.com/bangtran365/scCAN/issues |
| License: |
LGPL-2 | LGPL-2.1 | LGPL-3 [expanded from: LGPL] |
| URL: |
https://github.com/bangtran365/scCAN |
| NeedsCompilation: |
no |
| Materials: |
README, NEWS |
| CRAN checks: |
scCAN results |
Documentation:
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