getpvalue {GraphAT} | R Documentation |

## Function to obtain P values from the Edge permutation and Node
permutation tests respectively

### Description

The function takes as inputs two adjacency matrices. Let X denote the observed number of
edges in common between the two adjacency matrices. To
test the significance of the correlation between the two data sources,
the function performs N random edge permutations and random node
permutations respectively. For each permutation test, the function
outputs the proportion of N realizations that resulted in X edges or more at the intersection of the two datasources

### Usage

getpvalue(act.mat, nonact.mat, num.iterations = 1000)

### Arguments

`act.mat` |
Adjacency matrix corresponding to first data
source. That is, the i,j element of this matrix is 1 if data source
one specifies a functional link between genes i and j |

`nonact.mat` |
Adjacency matrix corresponding to first data
source. That is, the i,j element of this matrix is 1 if data source
two specifies a functional link between genes i and j |

`num.iterations` |
Number of realizations from random edge (node)
permutation to be obtained |

### Details

We note that the first adjacency matrix, denoted act.mat is
the data source that is permutated with respect to edges or notes

### Value

A vector of length 2, where the first element is the P value
from Random Edge Permutation and the second element is the P value
from Random Node Permutation

### Author(s)

Raji Balasubramanian

### See Also

`permEdgesM2M`

, `permNodesM2M`

, `makeClustM`

### Examples

act.mat <- matrix(0,3,3)
act.mat[2,1] <- 1
act.mat[3,1] <- 1
nonact.mat <- matrix(0,3,3)
nonact.mat[2,1] <- 1
nonact.mat[3,2] <- 1
p.val <- getpvalue(act.mat, nonact.mat, num.iterations = 100)
print(p.val)

[Package

*GraphAT* version 1.0.0

Index]