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>.

Package details

AuthorAnnice Najafi [aut, cre] (ORCID: <https://orcid.org/0000-0003-0679-9397>)
MaintainerAnnice Najafi <annicenajafi27@gmail.com>
LicenseMIT + file LICENSE
Version0.2
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("SurprisalAnalysis")

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SurprisalAnalysis documentation built on Sept. 10, 2025, 10:30 a.m.