PANR (version 1.18.0)

buildPAN: Build an igraph or RedeR graph for PAN

Description

The function builds a graph for the inferred PAN so that it can be visualize in igraph or RedeR

Usage

buildPAN(object, engine="igraph", para=list(nodeColor=NULL, nodeSize=NULL, 
edgeWidth=NULL, edgeColor=NULL, nodeSumCols=1, nodeSumMethod="none", 
hideNeg=TRUE), verbose=TRUE, ...)

Arguments

object

an object of S4 class PAN.

engine

a character value specifying which graphics engine to use: `igraph' or `RedeR'.

para

a list of parameters specifying graph attributes (see details)

verbose

a logical value to switch on (if TRUE) or off if FALSE detailed run-time message.

...

all the other arguments accepted by the function pvclust.

Value

This function will return an object of class PAN with inferred gene modules (modules$clusters) and corresponding p-values (modules$pval) updated in slot 'modules'.

Details

Here are the introductions for the detailed graph attributes that the user can specify:

'nodeColor' and 'nodeSize' - a vector of node colors or sizes. Please note that the order of color or size must be concordant with the gene ids in PANR:the argument pheno of the object of BetaMixture.

'nodeSumCols' and 'nodeSumMethod' - these two arguments are used to scale the colors of nodes by phenotypes. The former argument is a numeric vector specifying the columns in slot pheno of the object of class BetaMixture; while the latter one is a character value giving the method to summarize these columns of phenotypes: either 'mean' or 'median'.

'edgeColor' and 'edgeWidth' - a vector of edge colors or width.

'pValCutoff' - the argument is only used when what='module' and for module searching based on pvclust. Only significant modules will be displayed.

'minSize' and 'maxSize' - two arguments controlling the size of modules which will be used to filtered out modules that are too small or too large.

'hideNeg' - a logical value specifying whether or not to hide edges with negative associations

References

Xin Wang, Mauro Castro, Klaas W. Mulder and Florian Markowetz, Posterior association networks and enriched functional gene modules inferred from rich phenotypic perturbation screens, in preparation.

R. Suzuki and H. Shimodaira. Pvclust: an r package for assessing the uncertainty in hierarchical clustering. Bioinformatics, 22(12):1540, 2006.

Examples

data(bm, package="PANR")
pan<-new("PAN", bm1=bm1)
pan<-infer(pan, para=list(type="SNR", log=TRUE, sign=TRUE, cutoff=log(5)),
filter=FALSE, verbose=TRUE)
data(Bakal2007Cluster, package="PANR")
pan<-buildPAN(pan, engine="igraph", para=list(nodeColor=nodeColor, 
hideNeg=TRUE), verbose=TRUE)