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mnda

Multiplex Network Differential Analysis (MNDA)

v1.0.9 · Jan 25, 2023 · GPL (>= 3)

Description

Interactions between different biological entities are crucial for the function of biological systems. In such networks, nodes represent biological elements, such as genes, proteins and microbes, and their interactions can be defined by edges, which can be either binary or weighted. The dysregulation of these networks can be associated with different clinical conditions such as diseases and response to treatments. However, such variations often occur locally and do not concern the whole network. To capture local variations of such networks, we propose multiplex network differential analysis (MNDA). MNDA allows to quantify the variations in the local neighborhood of each node (e.g. gene) between the two given clinical states, and to test for statistical significance of such variation. Yousefi et al. (2023) <doi:10.1101/2023.01.22.525058>.

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NOTE 12 OK · 2 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE Mar 9, 2026
NOTE r-devel-linux-x86_64-fedora-clang

dependencies in R code

Namespaces in Imports field not imported from:
  ‘MASS’ ‘Matrix’ ‘magrittr’ ‘reticulate’ ‘tensorflow’ ‘usethis’
  All declared Imports should be used.
NOTE r-devel-linux-x86_64-fedora-gcc

dependencies in R code

Namespaces in Imports field not imported from:
  ‘MASS’ ‘Matrix’ ‘magrittr’ ‘reticulate’ ‘tensorflow’ ‘usethis’
  All declared Imports should be used.

Dependency Network

Dependencies Reverse dependencies assertthat igraph Matrix keras tensorflow reticulate MASS ggraph ggplot2 aggregation usethis magrittr mnda

Version History

new 1.0.9 Mar 9, 2026