micropan (version 1.0)

plot.Binomix: Plotting and printing Binomix objects

Description

Generic functions for plotting and printing the content of a Binomix object.

Usage

"plot"(x, type="pan", cex=2, ncomp=NA, ...)
"summary"(object, ...)
"str"(object, ...)

Arguments

x

A Binomix object, see below.

object

A Binomix object, see below.

type

Type of plot, default is type="pan" which means the pie chart shows distribution over the entire pan-genome. The alternative is type="single" which means the pie chart will show the distribution within a single (average) genome.

cex

Plot symbol scaling.

ncomp

Which model to display. You can override the display of the optimal (minimum BIC) model by specifying the number of components here, e.g. ncomp=5 will always display the model with 5 components regardless of its BIC value.

...

Optional graphical arguments.

Details

A Binomix object contains a series of fitted binomial mixture models. It is a small (S3) extension to a list, having two components. These are named BIC.table and Mix.list, see binomixEstimate for more details. The plot.Binomix function will display a Binomix object as a pie chart. Only the model with the smallest BIC-criterion value is displayed. The BIC-criterion is used to rank the various fitted models, and minimum BIC is an objective criterion for finding the best model complexity. Each sector of the pie chart is a component, the color of the sector indicates its detection probability and the size of the sector its mixing proportion. This pie chart illustrates how gene clusters are distributed within the pan-genome. Sectors of (dark) blue color are highly conserved gene clusters (core genes), sectors of greenish colors are medium conserved clusters (shell genes) and sectors of orange/pink colors are non-conserved clusters (cloud genes). The summary.Binomix function will print the estimated core size and pan-genome size for the optimal component model. The str.Binomix function will simply print the number of models fitted in the Binomix object.

See Also

binomixEstimate.

Examples

# See examples in the Help-file for binomixEstimate.