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mnda (version 1.0.9)

Multiplex Network Differential Analysis (MNDA)

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) .

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Version

Install

install.packages('mnda')

Monthly Downloads

187

Version

1.0.9

License

GPL (>= 3)

Maintainer

Behnam Yousefi

Last Published

January 25th, 2023

Functions in mnda (1.0.9)

mnda_embedding_2layer

Calculate the embedding space for a two layer multiplex network
mnda_node_detection_2layer

Detecting the nodes whose local neighbors change bweteen the two conditions.
p_val_rank

Calculate p.value for x given a null pdf using ranks
subgraph_plot

Visualization of a subgroup using a circular graph
subgraph_difference_plot

Visualization of a difference subgroup using a circular graph
mnda_node_distance

Detecting the nodes whose local neighbors change between the two conditions for ISNs.
as.mnda.graph

Convert adjacency matrix to mnda graph data
ednn_IOprepare

Preparing the input and output of the EDNN for a multiplex graph
mnda_embedding

Calculate the embedding space for a multiplex network
Distance

Function to calculate distance between two vectors
EDNN

Encoder decoder neural network (EDNN) function
WeightdRandomWalk

Weighted Random Walk algorithm
as.igraph

Convert mnda graph data to igraph
example_data

Example Data
network_gen

Multiplex Network Generation
p_val_norm

Calculate p.value for x given a Gaussian null pdf
mnda_distance_test_isn

Test the embedding distances of local neighbors change between the two conditions for ISNs.
RepRandomWalk

Repetitive Fixed-length (weighted) random walk algorithm
Rank

Ranking a vector