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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) &lt;<a href="https://doi.org/10.1016%2Fj.molmet.2021.101295" target="_top">doi:10.1016/j.molmet.2021.101295</a>&gt;.



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CoNI: Correlation Guided Network Integration (CoNI)

https://cran.r-project.org/web/packages/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) &lt;<a href="https://doi.org/10.1016%2Fj.molmet.2021.101295" target="_top">doi:10.1016/j.molmet.2021.101295</a>&gt;.



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https://cran.r-project.org/web/packages/CoNI

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) &lt;<a href="https://doi.org/10.1016%2Fj.molmet.2021.101295" target="_top">doi:10.1016/j.molmet.2021.101295</a>&gt;.

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      Correlation Guided Network Integration (CoNI) [R package CoNI version 0.1.0]
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      José Manuel Monroy Kuhn

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      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) &lt;<a href="https://doi.org/10.1016%2Fj.molmet.2021.101295" target="_top">doi:10.1016/j.molmet.2021.101295</a>&gt;.
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