runDEGraph: Run a topological analysis on an expression dataset using...

Description Usage Arguments Details References See Also Examples

Description

DEGraph implements recent hypothesis testing methods which directly assess whether a particular gene network is differentially expressed between two conditions.

Usage

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  runDEGraph(x, expr, classes, ...)

Arguments

x

a PathwayList, a list of Pathways or a single Pathway object.

expr

a matrix (size: number p of genes x number n of samples) of gene expression.

classes

a vector (length: n) of class assignments.

...

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

The expression data and the pathway have to be annotated in the same set of identifiers.

References

L. Jacob, P. Neuvial, and S. Dudoit. Gains in power from structured two-sample tests of means on graphs. Technical Report arXiv:q-bio/1009.5173v1, arXiv, 2010.

See Also

testOneGraph

Examples

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if (require(DEGraph)) {
  data("Loi2008_DEGraphVignette")

  b <- pathways("hsapiens", "biocarta")
  p <- convertIdentifiers(b[["actions of nitric oxide in the heart"]], "entrez")
  runDEGraph(p, exprLoi2008, classLoi2008)
}

graphite documentation built on May 31, 2017, 3:20 p.m.