README.Rmd

---
title: "README"
output:
  html_document:
    keep_md: yes
    self_contained: no
---

```{r, echo=FALSE}
info<-data.frame(read.table("version_info.txt",header=TRUE))
```

[MetaMapR](http://dgrapov.github.io/MetaMapR/) 
========

## A metabolomic network mapping tool 
![demo](Manual/metamapr_long.gif)

## [Screenshots](https://github.com/dgrapov/MetaMapR/blob/master/screenshots.md)

### Installation
Requires [R](http://cran.us.r-project.org/) and [Shiny](https://github.com/rstudio/shiny-server). 
Try it out using the [Shiny glimmer server](http://spark.rstudio.com/dgrapov/MetaMapR/) 
or run locally by pasting the following code into the R console:
```r
library(shiny)
shiny::runGitHub('MetaMapR','dgrapov')
```
Alternatively download the .zip file, unzip and run the following code (example for file on desktop)
```r
library(shiny)
shiny::runApp('~/../Desktop/MetaMapR-master/MetaMapR-master')
```
NOTE: modify file paths for OSX and LINUX 

### Instructions
* [Tutorial](http://ufpr.dl.sourceforge.net/project/metamapr/Metmapr%20v1.2.1%20tutorial%20v1.doc.pdf) (a more detailed version coming soon)
* [Examples](http://dgrapov.github.io/MetaMapR/)

### Information
Version: `r info$version` (`r info$date`)

News: [See the newest features.](https://github.com/dgrapov/MetaMapR/blob/master/NEWS.md)

License: GNU General Public License (v3), [read more](https://github.com/dgrapov/MetaMapR/blob/master/LICENSE)

### Citation
If you find MetaMapR useful please cite this tool using the doi listed below.

Dmitry Grapov (2014) MetaMapR: Metabolomic Network Analysis and Visualization Tool

[![DOI](https://zenodo.org/badge/7400/dgrapov/MetaMapR.png)](http://dx.doi.org/10.5281/zenodo.12880)

### TODO
* add partial correlations
* add cytoscape.js networks
* enable network mapping

### FAQ
1. How are multiple edge types handled in the network output?

The default setting for returning all edge types or only unique edges can be found under the network tab using the unique edges checkbox. If the option is selected then edges are returned based on a hierarchy Biochemical > Structural > Mass Spectral > Correlation, otherwise all edges are returned.