nodeTest {BioNetStat} | R Documentation

## Node score equality test

### Description

Nodes scores equality test between network

### Usage

    degreeCentralityVertexTest(expr, labels, adjacencyMatrix,
      numPermutations = 1000, options = NULL, BPPARAM = MulticoreParam())

    betweennessCentralityVertexTest(expr, labels, adjacencyMatrix,
      numPermutations = 1000, options = NULL, BPPARAM = MulticoreParam())

    closenessCentralityVertexTest(expr, labels, adjacencyMatrix,
      numPermutations = 1000, options = NULL, BPPARAM = MulticoreParam())

    eigenvectorCentralityVertexTest(expr, labels, adjacencyMatrix,
      numPermutations = 1000, options = NULL, BPPARAM = MulticoreParam())

    clusteringCoefficientVertexTest(expr, labels, adjacencyMatrix,
      numPermutations = 1000, options = NULL, BPPARAM = MulticoreParam())

### Arguments

`expr` | Matrix of variables (columns) vs samples (rows)
`labels` | a vector in which a position indicates the phenotype of the corresponding sample or state
`adjacencyMatrix` | a function that returns the adjacency matrix for a given variables values matrix
`numPermutations` | number of permutations that will be carried out in the permutation test
`options` | argument non used in this function
`BPPARAM` | An optional BiocParallelParam instance determining the parallel back-end to be used during evaluation, or a list of BiocParallelParam instances, to be applied in sequence for nested calls to BiocParallel functions.

### Value

A table, containing on the columns, the following informations for each variable (rows): "Test Statistic" - difference among the degree centrality of a node in two or more networks associated with each phenotype "Nominal p-value" - the Nominal p-value of the test "Q-value" - the q-value of the test, correction of p-value by FDR to many tests "Factor n" - the node degree centrality in each network compared

### Examples

    set.seed(1)
    expr <- as.data.frame(matrix(rnorm(120),40,30))
    labels<-rep(0:3,10)
    adjacencyMatrix1 <- adjacencyMatrix(method="spearman", association="pvalue",
     threshold="fdr", thr.value=0.05, weighted=FALSE)
    # The numPermutations number is 1 to do a faster example, but we advise to use unless 1000 permutations in real analysis

    # Degree centrality test
    degreeCentralityVertexTest(expr, labels, adjacencyMatrix1,numPermutations=1)

    # Betweenness centrality test
    betweennessCentralityVertexTest(expr, labels, adjacencyMatrix1,numPermutations=1)

    # Closeness centrality test
    closenessCentralityVertexTest(expr, labels, adjacencyMatrix1,numPermutations=1)

    # Eigenvector centrality test
    eigenvectorCentralityVertexTest(expr, labels, adjacencyMatrix1,numPermutations=1)

    # Clustering coefficient test
    clusteringCoefficientVertexTest(expr, labels, adjacencyMatrix1,numPermutations=1)

[Package BioNetStat version 1.0.4 Index]