MODERN

MODERN (MOdule DEtection and Refinement in signed Networks) detects and refines modules in networks containing positive and negative edges. The Python package is named modernsn, and the command-line program is modern.

MODERN provides signed modularity and signed Constant Potts Model clustering, metanode analysis, negative-edge-guided reintegration, hard cannot-link refinement, multi-seed negative-edge leverage, and practical signed-network diagnostics.

Installation

pip install modernsn==0.1.2

The core dependencies are NumPy, pandas, python-igraph, leidenalg, NetworkX, Matplotlib, seaborn, and EEISP. Optional dependencies can be installed for specific functions:

pip install "modernsn[mat]==0.1.2"         # MATLAB .mat input (SciPy)
pip install "modernsn[comparison]==0.1.2"  # partition ARI comparison (scikit-learn)
pip install "modernsn[scrna]==0.1.2"       # single-cell analysis (Scanpy)

Quick start

MODERN accepts separate positive and negative edge lists. The default TSV format has five columns and no header:

gene_id1    gene_id2    gene_name1    gene_name2    weight
ENSG00001   ENSG00002   GeneA         GeneB         15.3

Run signed Leiden modularity as follows:

modern --pos positive.tsv --neg negative.tsv \
  --thre-pos 10 --thre-neg 1 \
  --method leiden-mod-alpha --alpha 0.7 --resolution 1 \
  --seed 12345 --out-prefix results/run1

To inspect a network before selecting an analysis, run:

modern --pos positive.tsv --neg negative.tsv \
  --method leiden-mod-alpha --check-signed-network \
  --leverage-seeds 1 2 3 10 42 \
  --out-prefix results/network_check

Documentation

See the MODERN documentation for:

• command-line input, methods, refinement modes, and outputs;
• the Python API and parallel parameter sweeps;
• interpretation guidance; and
• runnable tutorials.

The example notebooks are available in examples/.

Citation

Nakato R., Nagai LAE, List M. MODERN: community detection and exclusivity-aware module refinement in signed biological networks. In preparation.