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 |
| DOI: |
10.32614/CRAN.package.CoNI |
| 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:
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