pnat

Network Analysis Tool around Python-Igraph Library for graph-theoretic parameters evaluation offering a variety of functions useful for bioinformatics including community detection and interactive visualisation of graph offering menu-driven simple to use an approach ( Initial version of code : https://github.com/nitinp14920914/igraphtool)

Table of contents

• Installation
• List of Files
• Network Analysis Tool Usage
• List of Functions
• Contact Information

Installation

Dependencies

python2.7/3.6
Matplotlib v3.1.1
python-igraph v0.7.1.post6
Networkx v2.3
pyvis v0.1.7.0

Matplotlib

Debian / Ubuntu :  sudo apt-get install python-matplotlib
Fedora / Redhat :  sudo yum install python-matplotlib

for pip
python -m pip install -U pip setuptools
python -m pip install matplotlib
python -m pip install pyvis

python-igraph

Debian / Ubuntu : sudo apt-get install python-igraph
Fedora / Redhat : sudo yum install python-igraph

using pip
pip install python-igraph

NetworkX

python -m pip install networkx

Pyvis

python -m pip install pyvis

List of Files

pnat.py
readme

Network Analysis Tool Usage

Usage

python pnat.py -format filename

For help

  python pnat.py -h or --help

• Enter the function number you want

• It Returns output for a selected function

• Network output files are written in graphml format

• A directory named temp is created on very first initialisation of script

• There is also a ./temp directory associated with pnat.py where plots/figures/are exported and saved

List of Functions

usage -format [filename]

format: adjacencncy matrix -adj  edgelist -edgelist  graphml -graphml  lgl -lgl  random network -random

=========== Feature List v1.0 =====================
Parameter Evaluation........................###
	Degree Distribution Histogram...........(1)
	Centrality : 
		* Eigenvector centrality........(2)
		* Betweenness centrality........(3)
	Average path length.....................(4)
	Degree distribution.....................(5)
	Clustering coefficient..................(6)
		* Average Clustering coefficient[1]
		* Each-nodes Clustering coeff.  [2]
	Shortest path between two nodes.........(7)
	Shortest path between all nodes.........(8)
	Degree distribution power law...........(9)
	Functional motifs......................(10)
	Modularity.............................(13)
	Connectivity : 
		vertex * For given two vertex..(14)
	       	       *Overall................(15)
		Edge   * For given two vertex..(16)
	       	       *Overall................(17)
	No. of clusters........................(18)
	Diameter...............................(23)
	Average path length....................(24)
	Giant_component Extraction.............(25)
Know-your Graph.............................###
	Maximum degree nodes.... ........... . (30)
	Minimum degree nodes.... ...........  .(31)
	Neighbour vertex : 
		* For two specified vertes.....(11)
		* For all vertex of graph......(12)
	Node label from its node id(Every node)(20)
	Node label from its node id(Every node)(21)
Saving/Writing Graph........................###
	Adjacency matrix.......................(19)
	Edgelist...............................(22)
	Interactive Plot.......................(34)
Editing Graph Data .........................###
	Add vertex(single)..............  ..   (26)
	Add vertices(many)..................   (27)
	Delete vertex(single)................ .(28)
	Delete vertices(many).... ........... .(29)
	Deleting all nodes saving in file .....(32)
Community Detection/Structure..........    .###
	Community Detection/Structure..........(33)
	* Community_walktrap           [1]
	* Compare_communities          [2]
	* Community_edge_betweenness   [3]
	* Community_infomap            [4]
	* Community_label_propagation  [5]

Contact Information

For any trouble and query feel free we would love to respond

• nitin53_sit@jnu.ac.in
• andrew@jnu.ac.in
• nitinp14920914@gmail.com