scenic-rs
Copyright (C) 2026 Nandor Laszik

This program is free software: you can redistribute it and/or modify it under
the terms of the GNU General Public License as published by the Free Software
Foundation, either version 3 of the License, or (at your option) any later
version. See the LICENSE file for the full text.

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Derivation and attribution
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scenic-rs is a Rust reimplementation of the SCENIC single-cell gene regulatory
network pipeline. It is a DERIVATIVE WORK of the following GPL-3.0 projects from
the Laboratory of Computational Biology (aertslab), VIB-KU Leuven, and is
therefore distributed under the GPL-3.0-or-later:

  * pySCENIC   - https://github.com/aertslab/pySCENIC   (GPL-3.0)
                 the GRNBoost2/GENIE3 + cisTarget (ctx) + AUCell workflow and the
                 module-generation / pruning logic (pyscenic/utils.py,
                 pyscenic/transform.py) were closely followed.
  * ctxcore    - https://github.com/aertslab/ctxcore    (GPL-3.0)
                 the cisTarget recovery-curve / AUC / NES math, ranking-database
                 layout, and regulon/gene-signature semantics (recovery.py,
                 rnkdb.py, ctdb.py, genesig.py) were reimplemented from.

GRN inference also follows the algorithms in arboreto and scikit-learn
(GENIE3 = random forests; GRNBoost2 = stochastic gradient boosting).

This is an independent project. It is not affiliated with, endorsed by, or an
official release of aertslab / VIB-KU Leuven.

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Please cite the original SCENIC work
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  Aibar et al. (2017) "SCENIC: single-cell regulatory network inference and
    clustering." Nature Methods 14, 1083-1086.
  Van de Sande et al. (2020) "A scalable SCENIC workflow for single-cell gene
    regulatory network analysis." Nature Protocols 15, 2247-2276.
  Moerman et al. (2019) "GRNBoost2 and Arboreto: efficient and scalable
    inference of gene regulatory networks." Bioinformatics 35, 2159-2161.
