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SelectSim Python

SelectSim infers evolutionary dependencies — co-mutations and mutual exclusivities — between functional alterations across cancer genomes. It estimates the expected co-mutation frequency for each gene pair from individual mutation frequencies and per-sample tumor mutation burden (TMB), then evaluates significance against a simulation-based null model.

SelectSim Method

This package accompanies the manuscript:

Iyer A, Petrovic M, Sesia D, Nanni L, Mina M, Ciriello G (2026). Evolving patterns of co-mutations from tumor initiation to metastatic progression. Nature Genetics. DOI: 10.1038/s41588-026-02661-4

Installation

cd SelectSim_py
uv sync                 # recommended; or: pip install -e .

Optional extras: uv sync --extra storage (Zarr on-disk storage), --extra docs (build docs locally), --all-extras. Supports Python 3.10-3.12.

Quick start

import selectsim as ss

# M, sample_class, alteration_class: see the Introduction tutorial for how
# to build these from a MAF, or load the bundled TCGA LUAD example data.
result = ss.selectX(
    M, sample_class, alteration_class,
    n_cores=1, min_freq=10, n_permut=1000,
)

# Significant evolutionary dependencies
significant = result['result'][result['result']['FDR']]

See the Introduction tutorial for a full walkthrough on real TCGA LUAD data, and docs/ for the full API reference (selectsim.gam for MAF ingestion, selectsim.plotting for visualization, selectsim.io for Parquet/Zarr storage).

Citation

If you use SelectSim in your research, please cite:

Iyer A, Petrovic M, Sesia D, Nanni L, Mina M, Ciriello G (2026). Evolving patterns of co-mutations from tumor initiation to metastatic progression. Nature Genetics. DOI: 10.1038/s41588-026-02661-4

Citation metadata is also available in CITATION.cff.

License

MIT License. See LICENSE.

Contact

For bugs or feature requests, use the issue tracker. This is the Python implementation of the SelectSim R package.

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A python package that implements the SelectSim methodology to infer evolutionary dependencies between functional alterations in cancer.

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