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: |
1.0.4 |
| Depends: |
R (≥ 3.5.0), scDHA, FNN, purrr |
| Imports: |
stats |
| Suggests: |
knitr |
| Published: |
2022-04-06 |
| 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 |
Documentation:
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