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RNentropy  

Entropy Based Method for the Detection of Significant Variation in Gene Expression Data
View on CRAN: Click here


Download and install RNentropy package within the R console
Install from CRAN:
install.packages("RNentropy")

Install from Github:
library("remotes")
install_github("cran/RNentropy")

Install by package version:
library("remotes")
install_version("RNentropy", "1.2.3")



Attach the package and use:
library("RNentropy")
Maintained by
Federico Zambelli
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2018-02-12
Latest Update: 2022-04-13
Description:
An implementation of a method based on information theory devised for the identification of genes showing a significant variation of expression across multiple conditions. Given expression estimates from any number of RNA-Seq samples and conditions it identifies genes or transcripts with a significant variation of expression across all the conditions studied, together with the samples in which they are over- or under-expressed. Zambelli et al. (2018) .
How to cite:
Federico Zambelli (2018). RNentropy: Entropy Based Method for the Detection of Significant Variation in Gene Expression Data. R package version 1.2.3, https://cran.r-project.org/web/packages/RNentropy. Accessed 25 Aug. 2026.
Previous versions and publish date:
(2026-07-09 08:19), 1.1.2 (2018-02-12 11:15), 1.2.0 (2018-03-02 15:35), 1.2.2 (2018-06-01 14:30)
Other packages that cited RNentropy R package
View RNentropy citation profile
Other R packages that RNentropy depends, imports, suggests or enhances
Complete documentation for RNentropy
Functions, R codes and Examples using the RNentropy R package
Some associated functions: RN_BarresLab_FPMK . RN_BarresLab_design . RN_Brain_Example_design . RN_Brain_Example_tpm . RN_calc . RN_calc_GPV . RN_calc_LPV . RN_pmi . RN_select . RNentropy-package . RNentropy . 
Some associated R codes: RN_calc.R . RN_calc_GPV.R . RN_calc_LPV.R . RN_pmi.R . RN_select.R . RNentropy-internal.R . RNentropy.R .  Full RNentropy package functions and examples
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