The hardware and bandwidth for this mirror is donated by dogado GmbH, the Webhosting and Full Service-Cloud Provider. Check out our Wordpress Tutorial.
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[@]dogado.de.

scCAN

scCAN is a R software package that can perform unsupervised clustering for single-cell RNA sequencing (scRNA-seq) data. scCAN overcomes the excessive noise level from scRNA-seq data by using autoencoders and accurately cluster the cells into correct cell types.

How to install:

• The package can be installed from this repository.
• Install devtools: utils::install.packages('devtools')
• Install the package using: devtools::install_github('bangtran365/scCAN') Or, install with manual and vignette: devtools::install_github('bangtran365/scCAN', build_manual = T, build_vignettes = T)

To run the sample example:

• Load the package: library(scCAN)
• Load SCE dataset: data('SCE'); data <- t(SCE$data); label <- as.character(SCE$cell_type1)
• Add log transformation: if(max(data)>100) data <- log2(data + 1)
• Generate clustering result, the input matrix has rows as samples and columns as genes: result <- scCAN(data, r.seed = 1)
• The clustering result can be found here: cluster <- result$cluster
• Calculating adjusted Rand Index: ari <- round(scCAN::adjustedRandIndex(cluster,label), 2)
• Print out ARI value: print(paste0("ARI = ", ari))

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.
Health stats visible at Monitor.