https://github.com/frankkramer-lab/mully
R package to create, modify and visualize graphs with multiple layers.
https://github.com/frankkramer-lab/mully
big-networks data-visualization graph-theory graphs igraph multilayer-networks node-colored-graphs
Last synced: 30 days ago
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R package to create, modify and visualize graphs with multiple layers.
- Host: GitHub
- URL: https://github.com/frankkramer-lab/mully
- Owner: frankkramer-lab
- Created: 2017-08-03T09:48:06.000Z (over 8 years ago)
- Default Branch: master
- Last Pushed: 2023-02-22T11:25:05.000Z (over 2 years ago)
- Last Synced: 2025-04-11T02:18:15.455Z (7 months ago)
- Topics: big-networks, data-visualization, graph-theory, graphs, igraph, multilayer-networks, node-colored-graphs
- Language: HTML
- Homepage:
- Size: 1.8 MB
- Stars: 45
- Watchers: 8
- Forks: 4
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
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README
# mully
## Introduction
Network theory has been used for many years in the modeling and analysis of complex systems, as epidemiology, biology and biomedicine . As the data evolves and becomes more heterogeneous and complex, monoplex networks become an oversimplification of the corresponding systems. This imposes a need to go beyond traditional networks into a richer framework capable of hosting objects and relations of different scales, called Multilayered Network
**Mully**, **mul**ti**l**a**y**er networks, is an R package that provides a multilayer network framework.
Using this package, the user can create, modify and visualize graphs with multiple layers. This package is an extension to the [igraph package](https://github.com/igraph/rigraph) that provides a monolayer graph framework.
The package is implemented as a part of [the Multipath Project](https://www.sys-med.de/en/junior-research-groups/multipath/) directed by [Dr. Frank Kramer](https://www.uni-augsburg.de/de/fakultaet/fai/informatik/prof/misit/mitarbeiter/) .
## Publication
More information and references can be found in the mully paper:
https://www.mdpi.com/2073-4425/9/11/519
## Installation
### Installation from CRAN
mully is now available on CRAN !!
[mully on CRAN](https://CRAN.R-project.org/package=mully)
### Installation via Github
```R
require(devtools)
install_github("frankkramer-lab/mully")
library(mully)
```
## Test the package
In this section, we provide a demo to test the package by calling some of the function. After running this script, you will have a graph g with 3 layers and 8 nodes. the graph can also be modified by calling other functions. Please refer to help to see the available functions.
### Create new mully graph
```R
g <- mully("MyFirstMully",direct = F)
```
### Add Layers
```R
g <- addLayer(g, c("Gene", "Drug", "Drug", "Disease"))
```
### Add/print Nodes
```R
g=addNode(g,"d1","disease",attributes=list(type="t1"))
print("Node d1 added as disease")
g=addNode(g,"d2","disease",attributes=list(type="t1"))
print("Node d2 added as disease")
g=addNode(g,"d3","disease",attributes=list(type="t1"))
print("Node d3 added as disease")
g=addNode(g,"dr1","drug",attributes=list(effect="strong"))
print("Node dr1 added as drug")
g=addNode(g,"dr2","drug",attributes=list(effect="strong"))
print("Node dr2 added as drug")
g=addNode(g,"dr3","drug",attributes=list(effect="moderate"))
print("Node dr3 added as drug")
g=addNode(g,"g1","gene",attributes=list(desc="AF"))
print("Node g1 added as gene")
g=addNode(g,"g2","gene",attributes=list(desc="BE"))
print("Node g2 added as gene")
#See vertices attributes
print(getNodeAttributes(g))
#The Result:
# name n type effect desc
# 1 d1 3 t1
# 2 d2 3 t1
# 3 d3 3 t1
# 4 dr1 2 strong
# 5 dr2 2 strong
# 6 dr3 2 moderate
# 7 g1 1 AF
# 8 g2 1 BE
```
### Add/print/remove Edges
```R
g=addEdge(g,"dr1","d2",list(name="treats"))
g=addEdge(g,"dr1","d2",list(name="extraEdge"))
g=addEdge(g,"d2","g1",list(name="targets"))
g=addEdge(g,"g2","dr3",list(name="mutates and causes"))
g=addEdge(g,"dr3","d3",list(name="treats"))
print(getEdgeAttributes(g)
#The Result:
# V1 V2 name
# 1 d2 dr1 treats
# 2 d2 dr1 extraEdge
# 3 d2 g1 targets
# 4 dr3 g2 mutates and causes
# 5 d3 dr3 treats
removeEdge(g,"d2","dr1",multi=T)
```
### Merge two graphs
```R
#Create a Second graph
g1=mully()
g1=addLayer(g1,c("protein","drug","gene"))
g1=addNode(g1,"dr4","drug",attributes=list(effect="strong"))
g1=addNode(g1,"dr5","drug",attributes=list(effect="strong"))
g1=addNode(g1,"dr6","drug",attributes=list(effect="moderate"))
g1=addNode(g1,"p1","protein")
g1=addNode(g1,"p2","protein")
g1=addNode(g1,"p3","protein")
g1=addNode(g1,"g3","gene")
g1=addNode(g1,"g4","gene")
g1=addEdge(g1,nodeStart = "p2",nodeDest = "p3",attributes = list(name="interacts"))
g1=addEdge(g1,nodeStart = "dr6",nodeDest = "g4",attributes = list(name="targets"))
#Merge both graphs
g12=merge(g,g1)
#Print the graph
print(g12)
# Printing this graph gives this result:
# mully -- MyFirstMully
# 4 Layers:
# ID Name NameLower
# 1 1 Gene gene
# 2 2 Drug drug
# 3 3 Disease disease
# 4 4 protein protein
#
# 16 Nodes:
# name n type effect desc
# 1 d1 3 t1
# 2 d2 3 t1
# 3 d3 3 t1
# 4 dr1 2 strong
# 5 dr2 2 strong
# 6 dr3 2 moderate
# 7 g1 1 AF
# 8 g2 1 BE
# 9 dr4 2 strong
# 10 dr5 2 strong
# 11 dr6 2 moderate
# 12 p1 4
# 13 p2 4
# 14 p3 4
# 15 g3 1
# 16 g4 1
#
# 7 Edges:
# V1 V2 name
# 1 d2 dr1 treats
# 2 d2 dr1 extraEdge
# 3 d2 g1 targets
# 4 dr3 g2 mutates and causes
# 5 d3 dr3 treats
# 6 p2 p3 interacts
# 7 dr6 g4 targets
```
### Visualization
```R
plot(g12,layout = "scaled")
```
```R
plot3d(g12)
```
## Available Functions
mully functions are divided into different files depending on their functionnality range:
[Constructor](https://github.com/frankkramer-lab/mully/blob/master/R/mully_constructor.R) ,
[Layers Functions](https://github.com/frankkramer-lab/mully/blob/master/R/mully_layer.R) ,
[Node Functions](https://github.com/frankkramer-lab/mully/blob/master/R/mully_node.R) ,
[Edge Functions](https://github.com/frankkramer-lab/mully/blob/master/R/mully_edge.R) ,
[Merge Function](https://github.com/frankkramer-lab/mully/blob/master/R/mully_merge.R) ,
[Visualization Functions](https://github.com/frankkramer-lab/mully/blob/master/R/mully_visualization.R) ,
[Import Functions](https://github.com/frankkramer-lab/mully/blob/master/R/mully_import.R) ,
[Export Functions](https://github.com/frankkramer-lab/mully/blob/master/R/mully_export.R) ,
[Demo](https://github.com/frankkramer-lab/mully/blob/master/R/mully_demo.R).
| Function |Description|
| --------------- |-----------|
|`mully(name,direct)`|Constructor Function, Create an empty multilayered graph|
|`print(g)`|Print function|
|`addLayer(g, nameLayer)`| Add a layer or a set of layers to a graph|
|`removeLayer(g, name,trans)`|Delete a layer or a set of layers from a graph|
|`isLayer(g, name)`|Verify if the layer exists in a graph|
|`getLayersCount(g)`|Get the number of layers in a graph|
|`getLayer(g, nameLayer)`|Get the nodes on a layer in a graph|
|`getNode(g,nameNode)`|Get a node from a graph|
|`getIDNode(g,nameNode)`|Get the id of a node|
|`addNode(g, nodeName, layerName, attributes)`|Add a node with assigned layer and attributes to a graph|
|`removeNode(g, name,trans)`|Delete a node or a set of nodes from a graph|
|`getNodeAttributes(g,nameNode)`|Get the attributes of one or all nodes|
|`addEdge(g, nodeStart, nodeDest, attributes)`|Add an edge|
|`removeEdge(g, nodeStart, nodeDest,attributes, multi)`|Delete an edge|
|`getEdgeAttributes(g,nodeStart,nodeDest)`|Get the attributes of the edges connecting two nodes or all the edges in the graph|
|`getIDEdge(g,nodeStart,nodeDest)`|Get the ids of the edges connecting two nodes|
|`merge(g1,g2)`|Merge or unite two graphs|
|`plot(g,layout)`|Plot the graph in 2D|
|`plot3d(g)`|Plot the graph in 3D using rgl|
|`importGraphCSV(name,direct,layers,nodes,edges)`|Import a mully graph from csv files|
|`importLayersCSV(g,file)`|Import layers to a mully graph from a CSV file|
|`importNodesCSV(g,file)`|Import nodes to a mully graph from a CSV file|
|`importEdgesCSV(g,file)`|Import edges to a mully graph from a CSV file|