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# MetaNetwork
Network analysis and visualization of proteomics data using weighted gene correlation network analysis. This file details how to run MetaNetwork. [MetaNetwork's wiki](https://github.com/smith-chem-wisc/MetaNetwork/wiki) contains an overview of the options available for MetaNetwork's WGCNA workflow and a vignette that details how to use and interpret MetaNetwork's results.
Network analysis and visualization of proteomics data using weighted gene correlation network analysis. This file details how to run MetaNetwork. [MetaNetwork's wiki](https://github.com/smith-chem-wisc/MetaNetwork/wiki) contains an overview of the options available for MetaNetwork's WGCNA workflow and a vignette that details how to use and interpret MetaNetwork's results.

## How to Run MetaNetwork

### (Reccomended) Run from Docker
## System Requirements
MetaNetwork requires:
* Docker: https://www.docker.com/get-started

## R Package Dependencies
MetaNetwork's R package dependencies are handled by renv, a version manager R package ensuring uniform package versioning when MetaNetwork is deployed. For a complete list of dependencies, please review the renv.lock file in this repository, found at this link: https://github.com/smith-chem-wisc/MetaNetwork/blob/master/renv.lock.

### Run from MetaNetwork via Docker

1. Download [Docker](https://docs.docker.com/get-docker/) compatible with your operating system.
2. Open Terminal (Mac) or Powershell (Windows).
3. Run the following code to download and launch MetaNetwork:

```
docker pull avc167/metanetwork:latest

docker run -p 3838:3838 avc167/metanetwork:latest
```
Open a web browser and type localhost:3838 (Windows) or 0.0.0.0:3838 into the search bar. MetaNetwork will now be visible.

Open a web browser and type localhost:3838 (Windows) or 0.0.0.0:3838 into the search bar. MetaNetwork's GUI will now be visible.


#### IMPORTANT NOTE FOR MAC USERS
Docker for MacOS requires users to allocate memory for its processes. If not enough memory is allocated to MetaNetwork, it will crash without warning or throwing an error message while processing data. To increase the amount of memory allocated to MetaNetwork, you must open the Docker Desktop application and navigate to settings (circled in red in the below image):
Docker for MacOS requires users to allocate memory for its processes. If not enough memory is allocated to MetaNetwork, it will crash without warning or error message. To increase the amount of memory allocated to MetaNetwork, you must open the Docker Desktop application and navigate to settings (circled in red in the below image):
![image](https://user-images.githubusercontent.com/64652734/133110120-874da43b-2db9-44e0-82c5-422b8f01a17e.png)

Then click Resources, and use the slider to increase the amount of memory and/or CPUs allocated to MetaNetwork's processes. Typically 10 GB of memory enables an analysis of ~8000 proteins without memory issues.
![image](https://user-images.githubusercontent.com/64652734/133110586-7799b2ec-ee56-49ef-bc46-f13d370e98ef.png)

## Using MetaNetwork
When running MetaNetwork for the first time, it will take a few moments to load the necessary R packages. The GUI will then be visible.
When running MetaNetwork for the first time in a container, it will take a few moments to load the necessary R packages. After a short period of time, the GUI will be visible.
![image](https://user-images.githubusercontent.com/64652734/114083377-816d8a00-9874-11eb-8e1b-113829b1c5be.png)

While running MetaNetwork, the R console will contain all the messages and any potential errors occuring. Once MetaNetwork is finished running, it will automatically generate plots and data tables in the WGCNA Diagnostics, Module Eigenprotein Analysis, g:Profiler Enrichment, and Data Analysis tabs. The data will also be downloadable under the Download tab.
While running MetaNetwork, the R console, viewable either from the terminal or the Docker Desktop app, will contain all the messages and/or errors. Once MetaNetwork is finished running, it will automatically generate plots and data tables in the WGCNA Diagnostics, Module Eigenprotein Analysis, g:Profiler Enrichment, and Data Analysis tabs. The data will also be downloadable under the Download tab.

### MetaNetwork Workflow
### Uploading data file
Expand All @@ -47,54 +56,5 @@ The second columns, Experiment, lists the experimental condition to which the sa
Finally, the UniProt Data Table upload should be a .tsv or .tab file downloaded from UniProt containing an Entry column, Protein name column, and Gene name column.
![image](https://user-images.githubusercontent.com/64652734/114087471-8d0f7f80-9879-11eb-9428-9cd8075f111e.png)



## Other ways to run MetaNetwork
### (Not recommended) Installing and running MetaNetwork via RStudio (Windows and MacOS)

1. Install [RStudio](https://www.rstudio.com)
2. Type the following commands into the console of RStudio to run MetaNetwork on either Windows or MacOS:

```
if(!require(shiny)) install.packages("shiny", dependencies = TRUE)
shiny::runGitHub("MetaNetwork", "smith-chem-wisc")
```

![image](https://user-images.githubusercontent.com/64652734/114083000-12903100-9874-11eb-9df8-97c2febd74af.png)

### (Not recommended) Installing and running MetaNetwork via RGui

1. Please see instructions below for setting up Pandoc in the system environment.
2. Then, MetaNetwork will be ready to run using the following commands:

```
install.packages("shiny")
shiny::runGitHub("MetaNetwork", "smith-chem-wisc")
```

![image](https://user-images.githubusercontent.com/64652734/114082840-dd83de80-9873-11eb-86cf-1f1e6bdac27b.png)

## System Requirements
MetaNetwork requires:
* R 4.0.2 or later
* RStudio 1.3.1073 (optional but recommended)

### MacOS
On MacOS, we recommend using RStudio to run MetaNetwork because the install.pandoc() command is not supported, complicating Pandoc installation. Fortunately, RStudio is packaged with its own Pandoc, so MetaNetwork will be fully functional on MacOS.

### Windows
If running in the RGui, MetaNetwork requires the installation of (Pandoc)[https://pandoc.org/] and (Rtools)[https://cran.r-project.org/bin/windows/Rtools/]. For Windows computers, run the following code in RGui to install Pandoc:

```
install.packages(c("installr", "rmarkdown"))
installr::install.pandoc()
```

Pandoc will begin downloading and require a restart before MetaNetwork will function correctly.
After the computer is restarted, open RGui again and run.
```
rmarkdown::find_pandoc()
```
This command should return the version and location of the Pandoc installation.

For Anaconda users: Due to a bug in RStudio, installations of RStudio from conda will not be able to find the Pandoc folder. As a result, we recommend downloading RStudio directly from the RStudio website.
### Encountering issues
Please submit any issues, including the full R terminal log from the terminal or Docker desktop, to the Issues page: https://github.com/smith-chem-wisc/MetaNetwork/issues.