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eCV  

Enhanced Coefficient of Variation and IDR Extensions for Reproducibility Assessment
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("eCV", "0.0.2")



Attach the package and use:
library("eCV")
Maintained by
Agustin Gonzalez-Reymundez
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2024-01-08
Latest Update: 2024-01-19
Description:
Reproducibility assessment is essential in extracting reliable scientific insights from high-throughput experiments. While the Irreproducibility Discovery Rate (IDR) method has been instrumental in assessing reproducibility, its standard implementation is constrained to handling only two replicates. Package 'eCV' introduces an enhanced Coefficient of Variation (eCV) metric to assess the likelihood of omic features being reproducible. Additionally, it offers alternatives to the Irreproducible Discovery Rate (IDR) calculations for multi-replicate experiments. These tools are valuable for analyzing high-throughput data in genomics and other omics fields. The methods implemented in 'eCV' are described in Gonzalez-Reymundez et al., (2023) .
How to cite:
Agustin Gonzalez-Reymundez (2024). eCV: Enhanced Coefficient of Variation and IDR Extensions for Reproducibility Assessment. R package version 0.0.2, https://cran.r-project.org/web/packages/eCV. Accessed 09 Oct. 2026.
Previous versions and publish date:
(2026-07-09 07:34), 0.0.1 (2024-01-08 11:30)
Other packages that cited eCV R package
View eCV citation profile
Other R packages that eCV depends, imports, suggests or enhances
Complete documentation for eCV
Functions, R codes and Examples using the eCV R package
Some associated functions: eCV . gIDR . mIDR . mrep_assessment . simulate_data . 
Some associated R codes: auxiliary_functions.R . eCV.R . eCV_jumpstart.R . gIDR.R . mIDR.R . mrep_assessment.R . simulate_data.R .  Full eCV package functions and examples
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