mfinder1.2-python

This notebook is python wrapper of network motif analyzer mfinder1.2(Milo et al. Science 2002). It has codes for the following steps and link them as a pipleline to analyze motif (subgraph) from network.

• Read graph from dictionary of NetworkX graph objects(.pkl) or directory containg graph files (/.gexf)

• Run mfinder1.2 on the graph data : this analyzes numbers in real/randomized network, z-score for each motif id

• Compute signifcance profile(SP; normalized z-score) based on mfinder1.2 result for each motif id

• Write result of step 2. and step 3. as csv(.csv) file

• Visualize significance profile of the network using pyplot

Reference

Every resources of directory mfinder1.2 is a clone of following work of Milo R. et al.

https://www.weizmann.ac.il/mcb/UriAlon/download/network-motif-software

Milo R, Shen-Orr S, Itzkovitz S, Kashtan N, Chklovskii D, Alon U. Network motifs: simple building blocks of complex networks. Science. 2002 Oct 25;298(5594):824-7. doi: 10.1126/science.298.5594.824. PMID: 12399590.

Dependencies

• networkx
• numpy
• pandas
• pickle
• os
• subprocess

Descriptions

• src/mfinder_python.ipynb

  • main wrapper notebook

• mfinder1.2

  • clone of original mfinder1.2 (https://www.weizmann.ac.il/mcb/UriAlon/download/network-motif-software)
  • readme.txt
    • Please refer to this readme file about details of mfinder program.
  • mfinder1.2/mfinderManual.pdf
    • Please refer to this manual about input/output format, arguement options and other details about mfinder program.
  • mfinder1.2/motifDictionary
    • Please refer to this dictionary about various motif structures and their id

• data

  • inputs should be manually placed here under dataset directory as data/[my_dataset_name]/[my_inputs]. There are 2 options of input file format. Please refer to src/mfinder_python.ipynb for details.
  • option 1. dictionary of NetworkX graph objects : data/[my_dataset_name]/[my_dictionary_name].pkl
  • option 2. directory of .gexf files : data/[my_dataset_name]/gexf/[my_gexf_name].gexf

• input

  • intermediate .txt files, which are automatically generated and is used as input for mfinder1.2.exe, are placed here.
  • You could either automatically write input files starting from files in data/[my_dataset_name] directory, or manually write .txt input files matching the input format of mfinder1.2 here.

• output

  • all the results including followings are generated here.
  • [file_name]_OUT.txt : mfinder1.2.exe's raw output file. You may refer to this files for overview of each analysis results
  • [file_name].jpg : single visualization of motif significance profile(SP) of all the indexed graphs. Please refer to section [Visualize Motif significance profile] of src/mfinder_python.ipynb for deatils.