get_hub_kleinberg {GWENA} | R Documentation

## Determine hub genes based on Kleinberg's score

### Description

Compute Kleinberg's score (defined as the principal eigenvector of A*t(A), where A is the similarity matrix of the graph) of each gene by module if provided or for whole network if not, and return the top_n highest ones.

### Usage

    get_hub_kleinberg(network, modules = NULL, top_n = 5, k_th = NULL)

### Arguments

`network` | matrix or data.frame, square table representing connectivity between each genes as returned by build_net. Can be whole network or a single module.
`modules` | list, modules defined as list of gene vectors. If null, network is supposed to be the whole network or an already split module
`top_n` | integer, number genes to be considered as hub genes
`k_th` | decimal, Kleinberg's score threshold above or equal to which genes are considered as hubs

### Details

If you provide a top_n value, you can't provide a k_th value and vice versa. If none of them is provided, top_n = 5. For more information on Kleinberg's score, look at `hub_score` from igraph.

### Value

A list of vectors, or single vector of gene names

### Examples

    mat <- matrix(runif(40*40), 40)
    colnames(mat) <- paste0("gene_", seq_len(ncol(mat)))
    rownames(mat) <- paste0("gene_", seq_len(nrow(mat)))
    get_hub_degree(mat)
    get_hub_kleinberg(mat, top_n = NULL, k_th = 0.9)

[Package GWENA version 1.0.1 Index]