runTopologyGSA {graphite} | R Documentation

## Run a topological analysis on an expression dataset using topologyGSA.

### Description

Use graphical models to test the pathway components highlighting those involved in its deregulation.

If the option `Ncpus` is set to a value larger than 1 and the package `parallel` is installed, the conversion procedure will automatically use multiple cores.

### Usage

      runTopologyGSA(x, test, exp1, exp2, alpha, ...)

### Arguments

`x` | a `PathwayList`, a list of `Pathway`s or a single `Pathway` object.
`test` | Either `"var"` and `"mean"`. Determine the type of test used by topologyGSA.
`exp1` | Experiment matrix of the first class, genes in columns.
`exp2` | Experiment matrix of the second class, genes in columns.
`alpha` | Significance level of the test.
`...` | Additional parameters forwarded to `topologyGSA`. When invoked on a `PathwayList`, can use the named option "maxNodes" to limit the analysis to those pathways having up to this given number of nodes.

### Details

This function produces a warning and returns NULL when the number of genes in common between the expression matrices and the pathway is less than 3.

### References

Massa MS, Chiogna M, Romualdi C. Gene set analysis exploiting the topology of a pathway. BMC System Biol. 2010 Sep 1;4:121.

### See Also

`pathway.var.test` `pathway.mean.test`

### Examples

    if (require(topologyGSA)) {
      data(examples)
      colnames(y1) <- paste("SYMBOL", colnames(y1), sep = ":")
      colnames(y2) <- paste("SYMBOL", colnames(y2), sep = ":")

      k <- pathways("hsapiens", "kegg")
      p <- convertIdentifiers(k[["Fc epsilon RI signaling pathway"]], "SYMBOL")
      runTopologyGSA(p, "var", y1, y2, 0.05)
    }

[Package graphite version 1.26.3 Index]