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README.Rmd
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---
output:
md_document:
variant: markdown_github
toc: true
toc_depth: 3
---
# POMAShiny <img src='app/mds/pix/logo.png' align='right' height='139'/>
<!-- badges: start -->
[](https://www.tidyverse.org/lifecycle/#stable)
[](https://github.com/pcastellanoescuder/POMAShiny/commits/master)
[](https://www.gnu.org/licenses/gpl-3.0)
<!-- badges: end -->
## Overview
POMAShiny is a web-based tool that provides a structured, flexible and user-friendly workflow for pre-processing, exploratory data analysis (EDA) and statistical analysis of metabolomics and proteomics data. This tool is based on the [**POMA**](http://pcastellanoescuder.github.io/POMA/) R/Bioconductor package, which increases the reproducibility and flexibility of the analysis outside the web environment. POMAShiny’s workflow is structured in four sequential and well-defined panels: 1) data upload, 2) pre-processing, 3) EDA and 4) statistical analysis panels. POMAShiny is hosted at https://webapps.nutrimetabolomics.com/POMAShiny.
<img src="inst/png/POMAShiny_demo.png" width="500%"/>
## Run POMAShiny locally
### Step 1: Clone this repository
Open the terminal and run:
```{bash, eval = FALSE}
git clone "https://github.com/pcastellanoescuder/POMAShiny.git"
```
### Step 2: Install package dependencies
Open the `POMAShiny.Rproj` with [RStudio](https://rstudio.com) and run:
```{r, eval = FALSE}
# CRAN packages
installifnot <- function(pckgName){
if (!(require(pckgName, character.only = TRUE))) {
install.packages(pckgName, dep = TRUE)
require(pckgName, character.only = TRUE)
}
}
pk1 <- c('shiny', 'DT', 'devtools', 'reshape2', 'plotly', 'fresh', 'shinyhelper', 'ggraph',
'rmarkdown', 'shinyWidgets', 'tidyverse', 'knitr', 'patchwork', 'BiocManager')
for (i in 1:length(pk1)){
installifnot(pk1[i])
}
# Install the old version of 'bs4Dash'
devtools::install_version("bs4Dash", version = "0.5.0", repos = "http://cran.us.r-project.org")
# Bioconductor packages
installBiocifnot <- function(pckgName){
if (!(require(pckgName, character.only = TRUE))) {
BiocManager::install(pckgName)
require(pckgName, character.only = TRUE)
}
}
pk2 <- c('Biobase', 'POMA', 'MSnbase')
for (i in 1:length(pk2)){
installBiocifnot(pk2[i])
}
```
NOTE: _POMAShiny was built with `bs4Dash` version 0.5.0 and is not compatible with newer versions of `bs4Dash` due to substantial breaking changes in the API. We keep the old version as indicated by the `bs4Dash` developers._
### Step 3: Deploy POMAShiny locally :tada:
Once all dependencies have been installed run the following command and enjoy the analysis!
```{r, eval = FALSE}
shiny::runApp(appDir = "app")
```
## Run POMAShiny Docker container image
### Step 1: Pull Docker image
Pull the POMAShiny Docker container image hosted at [Docker Hub](https://hub.docker.com/repository/docker/pcastellanoescuder/pomashiny) by running the following command in the terminal.
```{bash, eval = FALSE}
docker pull pcastellanoescuder/pomashiny:v.1.1.14
```
### Step 2: Run Docker image
Run the container on your terminal once it has been pulled.
```{bash, eval = FALSE}
docker run -d --rm -p 3838:3838 pomashiny
```
### Step 3: Run POMAShiny in your browser
Open your browser and paste `http://0.0.0.0:3838`. Then, enjoy the analysis!
## Code of Conduct
Please note that the POMAShiny project is released with a [Contributor Code of Conduct](https://contributor-covenant.org/version/2/0/CODE_OF_CONDUCT.html). By contributing to this project, you agree to abide by its terms.