The hardware and bandwidth for this mirror is donated by METANET, the Webhosting and Full Service-Cloud Provider.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]metanet.ch.

EGRNi: Ensemble Gene Regulatory Network Inference

Gene regulatory network constructed using combined score obtained from individual network inference method. The combined score measures the significance of edges in the ensemble network. Fisher's weighted method has been implemented to combine the outcomes of different methods based on the probability values. The combined score follows chi-square distribution with 2n degrees of freedom. <doi:10.22271/09746315.2020.v16.i3.1358>.

Version: 0.1.6
Depends: R (≥ 3.5.0)
Imports: fdrtool, gdata, MASS, readr, stats
Suggests: testthat (≥ 3.0.0)
Published: 2022-11-18
DOI: 10.32614/CRAN.package.EGRNi
Author: Chiranjib Sarkar ORCID iD [aut, cre, ctb], Dipayan Sarkar ORCID iD [aut], Rajender Parsad [aut], Dwijesh Mishra ORCID iD [aut]
Maintainer: Chiranjib Sarkar <cschiranjib9 at gmail.com>
License: GPL-3
NeedsCompilation: no
CRAN checks: EGRNi results

Documentation:

Reference manual: EGRNi.pdf

Downloads:

Package source: EGRNi_0.1.6.tar.gz
Windows binaries: r-devel: EGRNi_0.1.6.zip, r-release: EGRNi_0.1.6.zip, r-oldrel: EGRNi_0.1.6.zip
macOS binaries: r-release (arm64): EGRNi_0.1.6.tgz, r-oldrel (arm64): EGRNi_0.1.6.tgz, r-release (x86_64): EGRNi_0.1.6.tgz, r-oldrel (x86_64): EGRNi_0.1.6.tgz

Linking:

Please use the canonical form https://CRAN.R-project.org/package=EGRNi to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.