computeCliques {cliqueMS} | R Documentation

## Computes clique groups from a similarity network

### Description

This function splits the features in the network in clique groups. The cliques are fully connected components that have high similarity for inner edges and low similarity for edges outside the clique. This function finds the clique groups that better fit this criteria, moving nodes to different groups until we find the groups that have the best log-likelihood.

### Usage

    computeCliques(anclique, tol = 1e-05, silent = TRUE)

### Arguments

`anclique` | This function uses S4 'anClique' object. Gives warning if clique groups have already been computed.
`tol` | Minimum relative increase in log-likelihood to do a new round of log-likelihood maximisation.
`silent` | If 'FALSE' print on the console the log-likelihood maximization progress. Default is 'TRUE'.

### Value

It returns an 'anClique' object with the computed clique groups. It adds the column 'cliqueGroup' to the 'peaklist' in the 'anClique' object.

### See Also

`getCliques`

### Examples

    mzfile <- system.file("standards.mzXML", package = "cliqueMS")
    msSet <- xcms::xcmsSet(files = mzfile, method = "centWave",
      ppm = 15, peakwidth = c(5,20), snthresh = 10)
    ex.anClique <- createanClique(msSet)
    show(ex.anClique)
    netlist <- createNetwork(msSet, xcms::peaks(msSet), filter = TRUE)
    getNetanClique(ex.anClique) <- netlist$network
    computeCliques(ex.anClique)

[Package cliqueMS version 1.8.0 Index]