CeRNASeek (version 1.0)

ceRNA.Net: visualize and analyze the identified ceRNA-ceRNA network using ceRNA.Net function

Description

A downstream analysis function of ceRNAseekvisualize and analyze the identified ceRNA-ceRNA network, the network can be defined as weighted or un-weighted network.and the basic topological features (such as degree, closeness, betweenness and centrality) of the ceRNAs can be output.

Usage

ceRNA.Net(data, net_direct = TRUE, vertex_size = 20, v.label = TRUE,
         node_shape = "circle",n_color = "orange",E_weight = TRUE, ity = 1,
         label_cex = 2, label_color = "black",edge_color = "gray", 
         n_frame.color = "gray")

Arguments

data

A matrix of ceRNA interaction pairs identified by statistical identification methods selected by the user .

net_direct

A logical variable specifies a directed or undirected network.default (net_direct = TRUE).

vertex_size

a numeric vector to adjust the node size,default (vertex_size = 20).

v.label

Whether to display the label of the node.default (v.label = TRUE).

node_shape

A character vector is used to adjust the shape of the node,The selectable shape parameters are "circle","square","csquare","rectangle","crectangle","vrectangle","pie", "sphere","none".default (node_shape = "circle").

n_color

The character vector used to define the fill color of the node.

E_weight

A logical vector represents whether the network is a weighted network,default (E_weight = TRUE).

ity

A numeric vector defines whether the edge is a solid line or a dotted line,the possible values of the vector are c(1, 2), default (ity = 1).

label_cex

Specify the size of the node label font.

label_color

Specify the label color of the node.

edge_color

Specify the color of the network side.

n_frame.color

The character vector used to define the border color of the node.

Value

The output includes two parts: the network diagram of ceRNA interaction and the topology attribute information of the network.

• Network topology attributes include 5 types of information:

  • degree degree refers to the number of edges in the network directly connected to the node

  • closeness An indicator that describes the average distance of a node to all other nodes in the network.

  • betweenness The proportion of this node that appears in the shortest path between other nodes.

  • cluster coefficient Representing the dense connection nature between some nodes in the network

  • Eigenvector centrality Representing the characteristic vector centrality of the network.

Details

This function calls the igraph package. For specific parameter settings, please refer to the igrap help documentation. Note:All the arguments without default value must be assigned.

Examples

# NOT RUN {
##Display ceRNA interactions in a network format and output network topology attributes.
##The input file can be a list of [ceRNA] of the ceRNA.Lin result file, a list of [cesig] 
##for the result file identified by ceRNA.basic, or a list of [ceRNA_comP] in the result
##file identified by the ceRNA.cmi function.
##Here we apply the ceRNA list in the example file for CMI identification to 
##display the network and analyze the network topology properties.
ceRNA.Net(as.matrix(dataset[["Pre.ceRNA"]]),net_direct=TRUE,vertex_size=20,v.label = TRUE,
         node_shape="circle",n_color = "orange",E_weight=TRUE,ity=1,label_cex=2,
         label_color="black",edge_color="gray",n_frame.color = "gray")
# }