plot.cepa.all: plot the cepa.all object

Description

plot the cepa.all object

Usage

# S3 method for cepa.all
plot(x, id = NULL, cen = 1, type = c("graph", "null"), tool = c("igraph", "Rgraphviz"),
    node.name = NULL, node.type = NULL,
    adj.method = "none", only.sig = FALSE,
    cutoff = ifelse(adj.method == "none", 0.01, 0.05), ...)

Arguments

x: a cepa.all object
id: index or the name for the pathway
cen: index or the name for the centrality
type: If the aim is to plot single pathway, then this argument is to identify the kind of the plotting.
tool: Use which tool to visualize the graph. Choices are 'igraph' and 'Rgraphviz'
node.name: node.name for each node
node.type: node.type for each node
adj.method: method of p.adjust, available methods are "holm", "hochberg", "hommel", "bonferroni", "BH", "BY", "fdr", "none"
only.sig: whether to show all pathways. If just show significant pathways, the names for each significant pathway will be draw.
cutoff: cutoff for significance
...: other arguments

Author

Zuguang Gu <z.gu@dkfz.de>

Details

This function has two applications. First, it can draw heatmaps of p-values of all pathways under different centrality measurements. To do it, users should set x, adj.method, only.sig, cutoff arguments.

Second, it can draw figures of single pathway under specific centrality measurement. Under this circumstance, this function is just a wrapper of plot.cepa. To do it, users should set x, id, cen, type, tool, node.name and node.type arguments. The id and cen arguments are used to get single cepa object that sent to the plot function.

It must be noted that these two kinds of arguments should not be mixed.

There is also another popular method qvalue to adjust p-values. However, errors may occur when adjusting some kind of p-value list by qvalue. So qvalue was not implemented into CePa. But still users can override the default p.adjust to support qvalue by themselves, see the vignette.

Examples

Run this code

if (FALSE) {
data(PID.db)

# ORA extension
data(gene.list)
# will spend about 20 min
res.ora = cepa.all(dif = gene.list$dif, bk = gene.list$bk, pc = PID.db$NCI)
plot(res.ora)
plot(res.ora, id = 3)
plot(res.ora, id = 3, type = "null")

# GSA extension
# P53_symbol.gct and P53_cls can be downloaded from
# http://mcube.nju.edu.cn/jwang/lab/soft/cepa/
eset = read.gct("P53_symbol.gct")
label = read.cls("P53.cls", treatment="MUT", control="WT")
# will spend about 45 min
res.gsa = cepa.all(mat = eset, label = label, pc = PID.db$NCI)
plot(res.gsa)
plot(res.gsa, id = 3, cen = 2)
plot(res.gsa, id = 3, cen = 2, type = "null")
}