README.Rmd

---
title: Shiny SBM
output: github_document
---

<!-- Compiling paragraph: start -->
```{r, eval=FALSE, include = FALSE, echo = F}
rmarkdown::render(input = "README.Rmd",
                 output_format = rmarkdown::html_document(),
                 quiet = TRUE,output_dir = "inst/app/www/")
rmarkdown::render(input = "README.Rmd",
                 output_format = rmarkdown::md_document(),
                 quiet = TRUE)
```



```{r, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.path = "man/figures/README-",
  out.width = "100%"
)
```



<!-- badges: start -->
[![Lifecycle: experimental](https://img.shields.io/badge/lifecycle-experimental-orange.svg)](https://lifecycle.r-lib.org/articles/stages.html#experimental)
<!-- badges: end -->

`shinySbm` is a package containing a shiny application. This application is build for network analysis based on the `sbm` package made by Chiquet J, Donnet S and Barbillon P (2023) [CRAN](https://CRAN.R-project.org/package=sbm). It allow to apply and explore the outputs of a Stochastic Block Model. It is useful if you want to analyse your data (could be adjacency matrix or edges list) without `R` language knowledge or to learn the basic lines of the `sbm` package. 

The Stochastic Block Model is applied on network to simplify the information they gather, and help to visualize the main behaviours/categories/relations there is in your network. It's a latent model which identify significant groups with similar behaviour by gathering the network nodes. By this you could be able to know if your network is : hidding closed sub-communities, hierachized, or is having another specific structure. 

With this application you should be also able to : 

 - Easly run a Stochastic Block Model
 - Get some nice outputs as matrix and network plots organized by groups
 - Get a modelisation summary
 - Extract nodes lists associated with their groups


## How to use the Application

### With `R`

#### Installation

You can install the development version of shinySbm like so:

``` r
remotes::install_github("Jo-Theo/shinySbm")
```

The shinySbm package should be installed. 

#### Running The Application

From a new `R` session you can then run

``` r
shinySbm::run_app()
```

### With `docker`

#### Installation

If you are familiar to `docker`, you can also download the docker image by running the command :

``` bash
docker pull registry.forgemia.inra.fr/theodore.vanrenterghem/shinysbm:latest
```
#### Running The Application

Once installed you can run the command to launch the app :

``` bash
docker run -p 3838:3838 registry.forgemia.inra.fr/theodore.vanrenterghem/shinysbm:latest
```

And then from your browser find the address `http://localhost:3838/`

## Contact

Any questions, problems or comments regarding this application ?        
Contact us : [shiny.sbm.dev@gmail.com](shiny.sbm.dev@gmail.com)

## References

Chiquet J, Donnet S, Barbillon P (2023).  sbm: Stochastic Blockmodels. R package version 0.4.5,  
https://CRAN.R-project.org/package=sbm.