compCorrGraph {GOstats} | R Documentation |
Given a set of gene expression data (an instance of the
exprSet
class) this function computes a graph based on
correlations between the probes.
compCorrGraph(eSet, k = 1, tau = 0.6)
eSet |
An instance of the exprSet 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.
data(ALL) set.seed(123) gs = sample(1:dim(ALL@exprs)[1], 200) Tsub = ALL[gs, grep("^T", as.character(ALL$BT))] corrG = compCorrGraph(Tsub)