eisa (version 1.24.0)

gograph: Plot part of the Gene Ontology hierarchy

Description

These functions help creating a plot of the Gene Ontology hierarchy.

Usage

gograph (table, colbar.length = 30, label.cex = 1, alpha=1, abbrev=5, GOGRAPHS = NULL, go.terms = NULL)
gographPlot (graph, coords = FALSE, ...)

Arguments

table

A data frame with one column, containing the $p$-values of the enriched GO terms. The row names of the data frame should contain the GO ids.

colbar.length

Numeric scalar, the length of the color bar.

label.cex

Numeric scalar, factor for the label sizes, e.g. ‘2’ means double size compared to the default.

alpha

Alpha channel for the fill color of the vertices.

abbrev

Numeric scalar, the minimum length for the abbreviated GO ids.

GOGRAPHS,go.terms

These are for internal use only.

graph

An igraph graph, as returned by the gograph function.

coords

Logical scalar, whether to return the coordinates of the vertices on the plot.

...

Additional arguments. These are passed to plot.igraph.

Value

gograph returns an igraph object.gographPlot by default returns NULL, invisibly. If the coords argument is TRUE, then it returns the coordinates of the vertices on the plot.

Details

A GO plot can be created in two steps. gograph creates an igraph graph object that contains all the information about the plot; gographPlot creates the actual plot.

The two steps are needed, because gograph calculates the optimal size of the plot, and then a graphics device of this size can be created before calling gographPlot.

The optimal size is returned by gograph in the width and height graph attributes, these can be queried with

    G <- gograph(...)
    G$width
    G$height
  

References

The Gene Ontology Consortium. Gene ontology: tool for the unification of biology. Nat. Genet. May 2000;25(1):25-9. Bergmann S, Ihmels J, Barkai N: Iterative signature algorithm for the analysis of large-scale gene expression data Phys Rev E Stat Nonlin Soft Matter Phys. 2003 Mar;67(3 Pt 1):031902. Epub 2003 Mar 11.

See Also

The igraph0 package for more about igraph graphs.

Examples

data(ALLModulesSmall)
GO <- ISAGO(ALLModulesSmall)
gotab <- summary(GO$BP)[[1]][,"Pvalue",drop=FALSE]

G <- gograph(gotab)
if (interactive()) {
  x11(width=G$width/15, height=G$height/15)
  gographPlot(G)
}