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clustNet is an R package for network-based clustering of categorical data using a Bayesian network mixture model and optional covariate adjustment.
The package requires Rgraphviz and RBGL, which can be installed from Bioconductor as follows:
{r eval=FALSE} if (!requireNamespace("BiocManager", quietly = TRUE)) install.packages("BiocManager") BiocManager::install(c("Rgraphviz", "RBGL"))
The latest stable version of clustNet is available on CRAN and can be installed with
{r eval=FALSE} install.packages("clustNet") from within an R session. On a normal computer, this should take around 5-60 seconds, depending on how many of the required packages are already installed.
BiocManager::install(“remotes”)
Being hosted on GitHub, it is also possible to use the install_github tool from an R session to install the latest development version:
{r eval=FALSE} library("devtools") install_github("cbg-ethz/clustNet")
clustNet requires R >= 3.5.
```{r eval=FALSE} library(clustNet)
k_clust <- 3 # numer of clusters ss <- c(400, 500, 600) # samples in each cluster simulation_data <- sampleData(k_clust = k_clust, n_vars = 20, n_samples = ss) sampled_data <- simulation_data$sampled_data
cluster_results <- get_clusters(sampled_data, k_clust = k_clust)
library(ggplot2) library(ggraph) library(igraph) library(ggpubr)
plot_clusters(cluster_results)
library(car) library(ks) library(graphics) library(stats)
density_plot(cluster_results)
```
On a normal computer, the clustering should take around 2-4 minutes.
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.
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