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scCAN  

Single-Cell Clustering using Autoencoder and Network Fusion
View on CRAN: Click here


Download and install scCAN package within the R console
Install from CRAN:
install.packages("scCAN")

Install from Github:
library("remotes")
install_github("cran/scCAN")

Install by package version:
library("remotes")
install_version("scCAN", "1.0.5")



Attach the package and use:
library("scCAN")
Maintained by
Bang Tran
[Scholar Profile | Author Map]
First Published: 2021-07-12
Latest Update: 2023-03-11
Description:
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.
How to cite:
Bang Tran (2021). scCAN: Single-Cell Clustering using Autoencoder and Network Fusion. R package version 1.0.5, https://cran.r-project.org/web/packages/scCAN. Accessed 28 Feb. 2025.
Previous versions and publish date:
1.0.0 (2021-07-12 09:30), 1.0.1 (2021-07-19 10:00), 1.0.2 (2022-03-28 23:40), 1.0.3 (2022-03-30 09:20), 1.0.4 (2022-04-06 02:10)
Other packages that cited scCAN R package
View scCAN citation profile
Other R packages that scCAN depends, imports, suggests or enhances
Complete documentation for scCAN
Functions, R codes and Examples using the scCAN R package
Some associated functions: SCE . adjustedRandIndex . calculate_celltype_prob . curate_markers . find_markers . find_specific_marker . get_cluster_markers . scCAN . 
Some associated R codes: SNF.R . Utils.R . affinityMatrix.R . dist2.R . estimateNumberOfClustersGivenGraph.R . scCAN.R . spectralClustering.R .  Full scCAN package functions and examples
Downloads during the last 30 days
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