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Bimodularity Framework

Main code for the analysis of directed graph communities, or bicommunities.

If you use parts of this code and framework, please cite the following article:

A. Cionca, C.H.M. Chan, & D. Van De Ville, Community detection for directed networks revisited using bimodularity, Proc. Natl. Acad. Sci. U.S.A. 122 (35) e2500571122, https://doi.org/10.1073/pnas.2500571122 (2025).

Requirements

Data

C. elegans

C. elegans data can be accessed on WormAtlas.org under "Neuronal Connectivity II: by L.R. Varshney, B.L. Chen, E. Paniagua, D.H. Hall and D.B. Chklovskii" (see Varshney et al., 2011 for more information). All data used are summarized in ./data/celegans.

Human

All data used in the analysis of bicommunities of the directed human connectome are present in ./data/brain (see the brain data directory for further details).

Python 3.11.8

The environment can be easily installed using pip install -r requirements.txt, or alternatively with a new conda environment:

conda create -n bimodularity python==3.11.8
conda activate bimodularity
pip install -r requirements.txt

Note that compatiblity is ensured for python 3.11.8 - you may have to play with dependencies when using other versions.

Usage

All the code is compiled within the main bimodularity module which include:

  • dgsp for processing and analyses,
  • data_load for handling the datasets,
  • bimod_plot for visualization,
  • bundle for utilities specific to the analysis of white matter fiber bundles.

Replication of Cionca, et al., 2025

In ./notebooks/01-bimodularity, you may find the main figure (Bimodularity-Figures.ipynb) and supplementary (Bimodularity-Supplementary.ipynb) notebooks to reproduce the analyses and figures of the article.

The Bimodularity-Figures.ipynb notebook:

  • generates the canonical graphs,
  • loads the C. elegans data,
  • computes the bimodularity analyses,
  • and creates all the figures in the article.

The Bimodularity-Supplementary.ipynb notebook:

  • creates all the supplementary figures in the article.

Bicommunities of the Directed Connectome

In ./notebooks/02-brain_bicommunities, you may find the main figure (brainbicom-Figures.ipynb) and supplementary (brainbicom-Supplementary.ipynb) notebooks to produce the analyses and figures of bicommunities of the human brain.

The brainbicom-ConsensusClustering.ipynb notebook:

  • Computes the consensus matrix for specific settings of the bicommunity detection and for various definition of directed connectomes (later saved in ./data/brain/derivatives/consensus_clustering). Note that you NEED to first run this notebook to generate the consensus data (if not already present) before running the figures notebooks.

The brainbicom-Figures.ipynb notebook:

  • loads consensus data,
  • computes the analyses of bicommunity structure,
  • and creates all the visualizations.

The brainbicom-Supplementary.ipynb notebook:

  • creates additional figures.

All notebooks are self-sufficient and should run when using the run all command.