ceRNA.Net: visualize and analyze the identified ceRNA-ceRNA network...
In CeRNASeek: Identification and Analysis of ceRNA Regulation

Description Usage Arguments Details Value Examples

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.

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")

`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.

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.

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.

##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")

       degree closeness betweenness cluster coefficient Eigenvector centrality
GMFB        1 0.1111111           0                 NaN              0.3977508
PTEN        5 0.2000000           6                 0.1              1.0000000
JARID2      2 0.1250000           0                 1.0              0.6604422
KLC2        2 0.1250000           0                 1.0              0.6604422
RB1         1 0.1111111           0                 NaN              0.3977508
RCN1        1 0.1111111           0                 NaN              0.3977508