gograph {eisa} | R Documentation

## 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`.

### 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

### 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.

### Author(s)

Gabor Csardi csardi.gabor@gmail.com

### 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)
    }

[Package eisa version 1.36.0 Index]