edge_node_distance: Perform the distance distribution of paired nodes in edges...

edge_node_distanceR Documentation

Perform the distance distribution of paired nodes in edges across networks.

Description

This class is a wrapper for a series of analysis on the distance values of paired nodes in edges across networks, including distance matrix conversion, the differential test and the visualization.

Methods

Public methods


Method new()

Usage
edge_node_distance$new(
  network_list,
  dis_matrix = NULL,
  label = "+",
  with_module = FALSE,
  module_thres = 2
)
Arguments
network_list

a list with multiple networks; all the networks should be trans_network object created from trans_network class of microeco package.

dis_matrix

default NULL; the distance matrix of nodes, used for the value extraction; must be a symmetrical matrix with both colnames and rownames (i.e. feature names).

label

default "+"; "+" or "-" or c("+", "-"); the edge label used for the selection of edges.

with_module

default FALSE; whether show the module classification of nodes in the result.

module_thres

default 2; the threshold of the nodes number of modules remained when with_module = TRUE.

Returns

data_table, stored in the object

Examples
\donttest{
data(soil_amp_network)
data(soil_amp)
# filter useless features to speed up the calculation
node_names <- unique(unlist(lapply(soil_amp_network, function(x){colnames(x$data_abund)})))
filter_soil_amp <- microeco::clone(soil_amp)
filter_soil_amp$otu_table <- filter_soil_amp$otu_table[node_names, ]
filter_soil_amp$tidy_dataset()
# obtain phylogenetic distance matrix
phylogenetic_distance <- as.matrix(cophenetic(filter_soil_amp$phylo_tree))
# choose the positive labels
t1 <- edge_node_distance$new(network_list = soil_amp_network, 
	 dis_matrix = phylogenetic_distance, label = "+")
}

Method cal_diff()

Differential test across networks.

Usage
edge_node_distance$cal_diff(
  method = c("anova", "KW", "KW_dunn", "wilcox", "t.test")[1],
  ...
)
Arguments
method

default "anova"; see the following available options:

'anova'

Duncan's multiple range test for anova

'KW'

KW: Kruskal-Wallis Rank Sum Test for all groups (>= 2)

'KW_dunn'

Dunn's Kruskal-Wallis Multiple Comparisons, see dunnTest function in FSA package

'wilcox'

Wilcoxon Rank Sum and Signed Rank Tests for all paired groups

't.test'

Student's t-Test for all paired groups

...

parameters passed to cal_diff function of trans_alpha class of microeco package.

Returns

res_diff in object. See the Return of cal_diff function in trans_alpha class of microeco package.

Examples
\donttest{
t1$cal_diff(method = "wilcox")
}

Method plot()

Plot the distance.

Usage
edge_node_distance$plot(...)
Arguments
...

parameters pass to plot_alpha function of trans_alpha class of microeco package.

Returns

ggplot.

Examples
\donttest{
t1$plot(boxplot_add = "none", add_sig = TRUE)
}

Method clone()

The objects of this class are cloneable with this method.

Usage
edge_node_distance$clone(deep = FALSE)
Arguments
deep

Whether to make a deep clone.

Examples


## ------------------------------------------------
## Method `edge_node_distance$new`
## ------------------------------------------------


data(soil_amp_network)
data(soil_amp)
# filter useless features to speed up the calculation
node_names <- unique(unlist(lapply(soil_amp_network, function(x){colnames(x$data_abund)})))
filter_soil_amp <- microeco::clone(soil_amp)
filter_soil_amp$otu_table <- filter_soil_amp$otu_table[node_names, ]
filter_soil_amp$tidy_dataset()
# obtain phylogenetic distance matrix
phylogenetic_distance <- as.matrix(cophenetic(filter_soil_amp$phylo_tree))
# choose the positive labels
t1 <- edge_node_distance$new(network_list = soil_amp_network, 
	 dis_matrix = phylogenetic_distance, label = "+")


## ------------------------------------------------
## Method `edge_node_distance$cal_diff`
## ------------------------------------------------


t1$cal_diff(method = "wilcox")


## ------------------------------------------------
## Method `edge_node_distance$plot`
## ------------------------------------------------


t1$plot(boxplot_add = "none", add_sig = TRUE)


meconetcomp documentation built on Nov. 18, 2023, 5:06 p.m.