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# CITATION file created with {cffr} R package
# See also: https://docs.ropensci.org/cffr/
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cff-version: 1.2.0
message: 'To cite package "scGraphVerse" in publications use:'
type: software
license: GPL-3.0-only
title: 'scGraphVerse: scGraphVerse: A Gene Network Analysis Package'
version: 1.3.0
identifiers:
- type: doi
  value: 10.32614/CRAN.package.scGraphVerse
abstract: A package for inferring, comparing, and visualizing gene networks from single-cell
  RNA sequencing data. It integrates multiple methods (GENIE3, GRNBoost2, ZILGM, PCzinb,
  and JRF) for robust network inference, supports consensus building across methods
  or datasets, and provides tools for evaluating regulatory structure and community
  similarity. GRNBoost2 requires Python package 'arboreto' which can be installed
  using init_py(install_missing = TRUE). This package includes adapted functions from
  ZILGM (Park et al., 2021), JRF (Petralia et al., 2015), and learn2count (Nguyen
  et al. 2023) packages with proper attribution under GPL-2 license.
authors:
- family-names: Cecere
  given-names: Francesco
  email: francesco.cecerengs@gmail.com
  orcid: https://orcid.org/0000-0002-0329-0870
- family-names: Carissimo
  given-names: Annamaria
- family-names: De Canditiis
  given-names: Daniela
- family-names: Angelini
  given-names: Claudia
preferred-citation:
  type: manual
  title: 'scGraphVerse: A Gene Regulatory Network Analysis Package'
  authors:
  - family-names: Cecere
    given-names: Francesco
    email: francesco.cecerengs@gmail.com
    orcid: https://orcid.org/0000-0002-0329-0870
  year: '2024'
  notes: R package version 0.99.0
  url: https://ngsFC.github.io/scGraphVerse
repository: https://bioc.r-universe.dev
repository-code: https://github.com/ngsFC/scGraphVerse
commit: 9153b373555a0c4b952eaed4ca587cb6d952f867
url: https://ngsFC.github.io/scGraphVerse
date-released: '2026-04-28'
contact:
- family-names: Cecere
  given-names: Francesco
  email: francesco.cecerengs@gmail.com
  orcid: https://orcid.org/0000-0002-0329-0870
references:
- type: article
  title: Zero-inflated latent Gaussian mixture models for inference of gene regulatory
    networks
  authors:
  - family-names: Park
    given-names: Beomjin
  - family-names: Choi
    given-names: Hosik
  - family-names: Park
    given-names: Changyi
  journal: Bioinformatics
  year: '2021'
  volume: '37'
  doi: 10.1093/bioinformatics/btab293
  start: 3085-3092
- type: article
  title: Integrative random forest for gene regulatory network inference
  authors:
  - family-names: Petralia
    given-names: Francesca
  - family-names: Wang
    given-names: Pei
  - family-names: Yang
    given-names: Jiayu
  - family-names: Tu
    given-names: Zhidong
  journal: Bioinformatics
  year: '2015'
  volume: '31'
  doi: 10.1093/bioinformatics/btv268
  start: i197-i205
- type: article
  title: A new consensus-based method for biomarker discovery from networks
  authors:
  - family-names: Policastro
    given-names: Valeria
  - family-names: Righelli
    given-names: Dario
  - family-names: Carissimo
    given-names: Annamaria
  - family-names: Cutillo
    given-names: Luisa
  journal: BMC Bioinformatics
  year: '2021'
  volume: '22'
  doi: 10.1186/s12859-021-04441-8
  start: 1-18