Package: eCV 0.0.2

eCV: Enhanced Coefficient of Variation and IDR Extensions for Reproducibility Assessment

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) <doi:10.1101/2023.12.18.572208>.

Authors:Agustin Gonzalez-Reymundez [aut, cre]

eCV_0.0.2.tar.gz
eCV_0.0.2.zip(r-4.5)eCV_0.0.2.zip(r-4.4)eCV_0.0.2.zip(r-4.3)
eCV_0.0.2.tgz(r-4.4-any)eCV_0.0.2.tgz(r-4.3-any)
eCV_0.0.2.tar.gz(r-4.5-noble)eCV_0.0.2.tar.gz(r-4.4-noble)
eCV_0.0.2.tgz(r-4.4-emscripten)eCV_0.0.2.tgz(r-4.3-emscripten)
eCV.pdf |eCV.html
eCV/json (API)
NEWS

# Install 'eCV' in R:
install.packages('eCV', repos = c('https://agugonrey.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/eclipsebio/ecv/issues

On CRAN:

3.00 score 1 scripts 146 downloads 5 exports 9 dependencies

Last updated 10 months agofrom:ca23528a35. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 02 2024
R-4.5-winOKNov 02 2024
R-4.5-linuxOKNov 02 2024
R-4.4-winOKNov 02 2024
R-4.4-macOKNov 02 2024
R-4.3-winOKNov 02 2024
R-4.3-macOKNov 02 2024

Exports:eCVgIDRmIDRmrep_assessmentsimulate_data

Dependencies:codetoolsdigestfuturefuture.applyglobalsidrlistenvmvtnormparallelly

Introduction to the eCV package

Rendered fromeCV_vignette.Rmdusingknitr::rmarkdownon Nov 02 2024.

Last update: 2024-01-20
Started: 2024-01-09