R: Wrapper for MRNET method

run_mrnet {dnapath} | R Documentation

## Wrapper for MRNET method

### Description

Conducts co-expression analysis using MRNET (Meyer et al. 2007). Uses the implementation from the `minet` package (Meyer et al. 2008). Can be used for the `network_inference` argument in `dnapath`.

### Usage

    run_mrnet(x, estimator = "spearman", weights = NULL, ...)

### Arguments

`x` | A n by p matrix of gene expression data (n samples and p genes).
`estimator` | Argument is passed into `build.mim`.
`weights` | An optional vector of weights. This is used by `dnapath()` to apply the probabilistic group labels to each observation when estimating the group-specific network.
`...` | Additional arguments are ignored.

### Value

A p by p matrix of association scores.

### References

Meyer PE, Kontos K, Lafitte F, Bontempi G (2007). “Information-Theoretic Inference of Large Transcriptional Regulatory Networks.” EURASIP Journal on Bioinformatics and Systems Biology, 2007, 8–8.

Meyer PE, Lafitte F, Bontempi G (2008). “minet: A R/Bioconductor Package for Inferring Large Transcriptional Networks using Mutual Information.” BMC Bioinformatics, 9(1), 461.

### See Also

`run_aracne`, `run_bc3net`, `run_c3net`, `run_clr`, `run_corr`, `run_dwlasso`, `run_genie3`, `run_glasso`, `run_pcor`, and `run_silencer`

### Examples

    data(meso)
    data(p53_pathways)

    # To create a short example, we subset on two pathways from the p53 pathway list,
    # and will only run 3 permutations for significance testing.
    pathway_list <- p53_pathways[c(8, 13)]
    n_perm <- 3

    # Use this method to perform differential network analysis.
    # The parameters in run_mrnet() can be adjusted using the ... argument.
    # For example, the 'estimator' parameter can be specified as shown here.
    results <- dnapath(x = meso$gene_expression,
                       pathway_list = pathway_list,
                       group_labels = meso$groups,
                       n_perm = n_perm,
                       network_inference = run_mrnet,
                       estimator = "spearman")
    summary(results)

    # The group-specific association matrices can be extracted using get_networks().
    nw_list <- get_networks(results[[1]]) # Get networks for pathway 1.

    # nw_list has length 2 and contains the inferred networks for the two groups.
    # The gene names are the Entrezgene IDs from the original expression dataset.
    # Renaming the genes in the dnapath results to rename those in the networks.
    # NOTE: The temporary directory, tempdir(), is used in this example. In practice,
    #       this argument can be removed or changed to an existing directory
    results <- rename_genes(results, to = "symbol", species = "human",
                            dir_save = tempdir())
    nw_list <- get_networks(results[[1]]) # The genes (columns) will have new names.

    # (Optional) Plot the network using SeqNet package (based on igraph plotting).
    # First rename entrezgene IDs into gene symbols.
    SeqNet::plot_network(nw_list[[1]])

[Package dnapath version 0.7.4 Index]