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
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
