Package: SurprisalAnalysis
Title: Information Theoretic Analysis of Gene Expression Data
Version: 3.0.0
Authors@R: 
    person("Annice", "Najafi", , "annicenajafi27@gmail.com", role = c("aut", "cre"),
           comment = c(ORCID = "0000-0003-0679-9397"))
Description: 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, capturing coordinated gene expression patterns under different biological conditions. References: Kravchenko-Balasha N. et al. (2014) <doi:10.1371/journal.pone.0108549>. Zadran S. et al. (2014) <doi:10.1073/pnas.1414714111>. Su Y. et al. (2019) <doi:10.1371/journal.pcbi.1007034>. Bogaert K. A. et al. (2018) <doi:10.1371/journal.pone.0195142>.
License: MIT + file LICENSE
Encoding: UTF-8
RoxygenNote: 7.3.3
Suggests: knitr, rmarkdown, pheatmap, peakRAM, data.table, BiocManager,
        org.Hs.eg.db, org.Mm.eg.db
VignetteBuilder: knitr
Imports: tidyr, dplyr, matlib, tidyverse, clusterProfiler,
        AnnotationDbi, shiny, ggplot2, shinythemes, shinyWidgets,
        shinyjs, shinycssloaders, patchwork, DT, httpuv
NeedsCompilation: no
Packaged: 2026-01-07 21:29:26 UTC; annic
Author: Annice Najafi [aut, cre] (ORCID:
    <https://orcid.org/0000-0003-0679-9397>)
Maintainer: Annice Najafi <annicenajafi27@gmail.com>
Repository: CRAN
Date/Publication: 2026-01-08 03:30:02 UTC
Built: R 4.5.3; ; 2026-04-14 04:50:25 UTC; windows
