mnda (version 1.0.9)

mnda_node_detection_2layer: Detecting the nodes whose local neighbors change bweteen the two conditions.

Description

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

Usage

mnda_node_detection_2layer(
  embeddingSpaceList,
  p.adjust.method = "none",
  alpha = 0.05,
  rank.prc = 0.1,
  volcano.plot = TRUE,
  ranksum.sort.plot = FALSE
)

Value

the highly variable nodes

Arguments

embeddingSpaceList

a list obtained by the mnda_embedding_2layer() function.

p.adjust.method

method for adjusting p-value (including methods on p.adjust.methods). If set to "none" (default), no adjustment will be performed.

alpha

numeric value of significance level (default: 0.05)

rank.prc

numeric value of the rank percentage threshold (default: 0.1)

volcano.plot

boolean value for generating the Volcano plot (default: TRUE)

ranksum.sort.plot

boolean value for generating the sorted rank sum plot (default: FALSE)

Details

Calculating the distance of node pairs in the embedding space and check their significance. To find the significantly varying nodes in the 2-layer-network, the distance between the corresponding nodes are calculated along with the null distribution. The null distribution is obtained based on the pairwise distances on null graphs. if in mnda_embedding_2layer function null.perm=FALSE, the multiplex network does not have the two randomly permuted graphs, thus the distances between all the nodes will be used for the null distribution.

Examples

myNet = network_gen(N_nodes = 50, N_var_nodes = 5, N_var_nei = 40, noise_sd = .01)
graph_data = myNet[["data_graph"]]
embeddingSpaceList = mnda_embedding_2layer(graph.data=graph_data, train.rep=5, walk.rep=5)
Nodes = mnda_node_detection_2layer(embeddingSpaceList)