buildPAN {PANR} | R Documentation

## 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`.

### 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

### 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'.

### Author(s)

Xin Wang xw264@cam.ac.uk

### 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)

[Package PANR version 1.32.0 Index]