# --------------------------------------------
# CITATION file created with {cffr} R package
# See also: https://docs.ropensci.org/cffr/
# --------------------------------------------
 
cff-version: 1.2.0
message: 'To cite package "CellOracleR" in publications use:'
type: software
license: Apache-2.0
title: 'CellOracleR: In Silico Gene Perturbation Analysis with Single-Cell Data'
version: 0.1.0
doi: 10.32614/CRAN.package.CellOracleR
abstract: An R implementation of the CellOracle framework for in silico gene perturbation
  analysis and gene regulatory network (GRN) inference from single-cell RNA-seq data.
  Predicts cell state transitions in response to transcription factor perturbations
  by combining GRN models with single-cell expression data. Key features include motif
  analysis for base GRN construction, cluster-specific GRN inference using regularized
  regression, perturbation simulation with signal propagation, and comprehensive visualization
  of predicted cell fate changes. Based on the methodology described in Kamimoto et
  al. (2023) <https://doi.org/10.15252/msb.202211547>.
authors:
- family-names: Liu
  given-names: Zaoqu
  email: liuzaoqu@163.com
repository: https://zaoqu-liu.r-universe.dev
repository-code: https://github.com/Zaoqu-Liu/CellOracleR
commit: e60a1b9d84a1b89c2e8f36efc8ea16065f673b57
url: https://github.com/Zaoqu-Liu/CellOracleR
date-released: '2026-01-24'
contact:
- family-names: Liu
  given-names: Zaoqu
  email: liuzaoqu@163.com