# --------------------------------------------
# CITATION file created with {cffr} R package
# See also: https://docs.ropensci.org/cffr/
# --------------------------------------------
 
cff-version: 1.2.0
message: 'To cite package "SurprisalAnalysis" in publications use:'
type: software
license: MIT
title: 'SurprisalAnalysis: Information Theoretic Analysis of Gene Expression Data'
version: '0.2'
doi: 10.32614/CRAN.package.SurprisalAnalysis
abstract: Implements Surprisal Analysis for gene expression data such as RNA-seq or
  microarray experiments. Surprisal Analysis is an information-theoretic method that
  decomposes gene expression data into a baseline state and constraint-associated
  deviations, which helps to capture coordinated gene expression patterns under different
  biological conditions. References where Surprisal analysis has been used for analyzing
  gene expression data (using the same methodology provided within this R package)
  are Kravchenko-Balasha et al (2014) <https://doi.org/10.1371/journal.pone.0108549>,
  Zadran et al. (2014) <https://doi.org/10.1073/pnas.1414714111>, Su et al. (2019)
  <https://doi.org/10.1371/journal.pcbi.1007034>, Bogaert et al. (2018) <https://doi.org/10.1371/journal.pone.0195142>.
authors:
- family-names: Najafi
  given-names: Annice
  email: annicenajafi27@gmail.com
  orcid: https://orcid.org/0000-0003-0679-9397
repository: https://annicenajafi.r-universe.dev
commit: a3909284ac45fa85f270e618db252a40c54e1748
date-released: '2025-09-10'
contact:
- family-names: Najafi
  given-names: Annice
  email: annicenajafi27@gmail.com
  orcid: https://orcid.org/0000-0003-0679-9397