This **R package** gathers a comprehensive set of algorithms to perform bioregionalisation analyses.

Bioregionalisation methods can be based on hierarchical clustering algorithms, non-hierarchical clustering algorithms or network algorithms.

The package can be installed with the following command line in R session:

From the CRAN

or from GitHub

We wrote several vignettes that will help you using the **bioregion R package**. Vignettes available are the following ones:

**1. Installation of the executable binary files**

**2. Matrix and network formats****3. Pairwise similarity/dissimilarity metrics****4.1 Hierarchical clustering****4.2 Non-hierarchical clustering****4.3 Network clustering****4.4 Microbenchmark****5.1 Visualization****5.2 Compare partitions**

Alternatively, if you prefer to view the vignettes in R, you can install the package with `build_vignettes = TRUE`

. But be aware that some vignettes can be slow to generate.

```
remotes::install_github("bioRgeo/bioregion",
dependencies = TRUE, upgrade = "ask",
build_vignettes = TRUE)
vignette("bioregion")
```

An overview of all functions and data is given **here**.

Thank you for finding it. Head over to the GitHub Issues tab and let us know about it. Alternatively, you can also send us an e-mail. We will try to get to it as soon as we can!

`bioregion`

depends on `ape`

, `bipartite`

, `cluster`

, `data.table`

, `dbscan`

, `dynamicTreeCut`

, `earth`

, `fastcluster`

, `ggplot2`

, `grDevices`

, `igraph`

, `mathjaxr`

, `Matrix`

, `Rcpp`

, `Rdpack`

, `rlang`

, `rmarkdown`

, `segmented`

,`sf`

, `stats`

, `tidyr`

and `utils`

.