CoNI: Correlation Guided Network Integration (CoNI)

Integrates two numerical omics data sets from the same samples using partial correlations. The output can be represented as a network, bipartite graph or a hypergraph structure. The method used in the package refers to Klaus et al (2021) <doi:10.1016/j.molmet.2021.101295>.

Version: 0.1.0
Depends: R (≥ 4.0)
Imports: igraph (≥ 1.2.6), doParallel (≥ 1.0.16), cocor (≥ 1.1.3), ggplot2 (≥ 3.3.3), forcats (≥ 0.5.1), dplyr (≥ 1.0.5), data.table (≥ 1.13.7), tibble (≥ 3.1.0), foreach (≥ 1.5.1), genefilter (≥ 1.72.1), ggrepel (≥ 0.9.1), gplots (≥ 3.1.1), gridExtra (≥ 2.3), plyr (≥ 1.8.6), ppcor (≥ 1.1), tidyr (≥ 1.1.3), Hmisc (≥ 4.4.2), methods (≥ 4.0.3), rlang (≥ 0.4.10), tidyselect (≥ 1.1.0)
Suggests: kableExtra (≥ 1.3.2), knitr (≥ 1.31), rmarkdown (≥ 2.6)
Published: 2021-09-30
Author: José Manuel Monroy Kuhn [aut, cre], Dominik Lutter [ths], Valentina Klaus [ctb]
Maintainer: José Manuel Monroy Kuhn <nolozz at gmail.com>
License: GPL-3
NeedsCompilation: no
SystemRequirements: python3
Citation: CoNI citation info
CRAN checks: CoNI results

Documentation:

Reference manual: CoNI.pdf
Vignettes: CoNI

Downloads:

Package source: CoNI_0.1.0.tar.gz
Windows binaries: r-devel: CoNI_0.1.0.zip, r-release: CoNI_0.1.0.zip, r-oldrel: CoNI_0.1.0.zip
macOS binaries: r-release (arm64): CoNI_0.1.0.tgz, r-release (x86_64): CoNI_0.1.0.tgz, r-oldrel: not available

Linking:

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