compCorrGraph: A function to compute a correlation based graph from Gene...
In GOstats: Tools for manipulating GO and microarrays

Description Usage Arguments Details Value Author(s) References See Also Examples

Given a set of gene expression data (an instance of the ExpressionSet class) this function computes a graph based on correlations between the probes.

1	compCorrGraph(eSet, k = 1, tau = 0.6)

`eSet`	An instance of the `ExpressionSet` class.
`k`	The power to raise the correlations to.
`tau`	The lower cutoff for absolute correlations.

Zhou et al. describe a method of computing a graph between probes (genes) based on estimated correlations between probes. This function implements some of their methods.

Pearson correlations between probes are computed and then these are raised to the power k. Any of the resulting estimates that are less than tau in absolute value are set to zero.

An instance of the graph class. With edges and edge weights determined by applying the algorithm described previously.

R. Gentleman

Zhou et al., Transitive functional annotation by shortest-path analysis of gene expression data.

compGdist

 ## Create an ExpressionSet to work with
 set.seed(123)
 exprMat <- matrix(runif(50 * 5), nrow=50)
 genData <- new("ExpressionSet", exprs=exprMat)

 corrG = compCorrGraph(genData)