comp.rand.subnet: Comparing a sub network to the randomly simulated ones In ProNet: Biological Network Construction, Visualization and Analyses

Description

Comparing a sub network with randomly simulated ones from the whole network.

Usage

 ```1 2 3``` ```comp.rand.subnet(subgraph, graph, nsim = 1000, degree = FALSE, betweenness = FALSE, ave.path.len = FALSE, eccentricity = FALSE, cc = FALSE, method = "utest", FDR = 0.05) ```

Arguments

 `subgraph` An igraph object. `graph` An igraph object. The whole one for random simulation. `nsim` Times for simulation. Default value is `1000`. `degree` Logical value, indicating whether to do vertex degree comparing (if `TRUE`) or not (if `FALSE`). `betweenness` Logical value, indicating whether to do betweenness comparing (if `TRUE`) or not (if `FALSE`). `ave.path.len` Logical value, indicating whether to do average path comparing (if `TRUE`) or not (if `FALSE`). `eccentricity` Logical value, indicating whether to do eccentricity comparing (if `TRUE`) or not (if `FALSE`). `cc` Logical value, indicating whether to do clustering coefficient comparing (if `TRUE`) or not (if `FALSE`). `method` Test method, currently only `utest` is supported. `FDR` False discovery rate. Default value is `0.05`.

Value

A matrix of compared parameters and plots.

References

Y Benjamini, Y Hochberg. Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing. Journal of the Royal Statistical Society. Series B (Methodological), Vol. 57, No. 1. (1995), pp. 289-300.

`net.comparing`, `comp.subnet`
 ```1 2 3 4``` ```g<-barabasi.game(100,power=0.8,directed=FALSE) subg<-induced.subgraph(g,sample(1:100,30)) comp.rand.subnet(subg,g) comp.rand.subnet(subg,g,degree=TRUE) ```