SurprisalAnalysis: Information Theoretic Analysis of Gene Expression Data

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>.

Version:	0.2
Imports:	tidyr, dplyr, matlib, org.Mm.eg.db, org.Hs.eg.db, clusterProfiler, AnnotationDbi, tidyverse, shiny, ggplot2, latex2exp, shinythemes, shinyWidgets, shinyjs, shinycssloaders, patchwork, DT, httpuv
Suggests:	knitr, rmarkdown, pheatmap, peakRAM, data.table
Published:	2025-09-10
Author:	Annice Najafi [aut, cre]
Maintainer:	Annice Najafi <annicenajafi27 at gmail.com>
License:	MIT + file LICENSE
NeedsCompilation:	no
Materials:	README
CRAN checks:	SurprisalAnalysis results

Documentation:

Reference manual:	SurprisalAnalysis.html , SurprisalAnalysis.pdf
Vignettes:	Comparisons of Normalization Methods (source, R code) Run Time Recording (source, R code) Surprisal analysis guidelines (source, R code)

Downloads:

Package source:	SurprisalAnalysis_0.2.tar.gz
Windows binaries:	r-devel: not available, r-release: not available, r-oldrel: not available
macOS binaries:	r-release (arm64): not available, r-oldrel (arm64): not available, r-release (x86_64): not available, r-oldrel (x86_64): SurprisalAnalysis_0.2.tgz

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