NetCoupler: Inference of Causal Links Between a Network and an External Variable

The 'NetCoupler' algorithm identifies potential direct effects of correlated, high-dimensional variables formed as a network with an external variable. The external variable may act as the dependent/response variable or as an independent/predictor variable to the network.

Version: 0.1.0
Depends: R (≥ 3.5.0)
Imports: checkmate, dplyr, ids, igraph, lifecycle, magrittr, pcalg, ppcor, purrr, rlang (≥ 0.4.6), stats, tibble, tidyselect, utils, tidygraph
Suggests: broom, furrr, knitr, rmarkdown, spelling, testthat (≥ 2.1.0)
Published: 2022-04-08
DOI: 10.32614/CRAN.package.NetCoupler
Author: Luke Johnston ORCID iD [aut, cre, cph], Clemens Wittenbecher ORCID iD [aut], Fabian Eichelmann [ctb], Helena Zacharias [ctb], Daniel Ibsen ORCID iD [ctb]
Maintainer: Luke Johnston <lwjohnst at>
License: MIT + file LICENSE
NeedsCompilation: no
Language: en-US
Materials: README NEWS
CRAN checks: NetCoupler results


Reference manual: NetCoupler.pdf
Vignettes: Getting started with NetCoupler


Package source: NetCoupler_0.1.0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): NetCoupler_0.1.0.tgz, r-oldrel (arm64): NetCoupler_0.1.0.tgz, r-release (x86_64): NetCoupler_0.1.0.tgz, r-oldrel (x86_64): NetCoupler_0.1.0.tgz


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