plot_exprs_vs_detection-methods: plot_exprs_vs_detection
In drmjc/microarrays: A collection of microarray and genomic helper code.

Description Arguments Value Author(s) Examples

From a set of expression data, make one 2-panel-plot for each probe in probes, where the top panel is the sorted expression levels, from low to high, and the bottom panel is the detection p-values. Datapoints are “x” or “o” depdending on whether they are above or below the detection.thresh. Optionally, certain named samples can the highlighted in red. A percentile axis is added to the top of the top panel. If you supply more than 1 probe, then multiple plots will be displayed. If you leave mains=missing, then you must specify gene.column, as the column name within fData(x)[,gene.column] which contains gene symbols. It's been designed to display large numbers of samples.

`x`	an ExpressionSet object
`probes`	a character vector of at least 1 probe ID. must be in `featureNames(x)`
`samples`	an optional vector of sample names to highlight in the plot
`detection.thresh`	an optional detection threshold for calling 'detected' genes
`mains`	an optional plot title(s). If missing, then the plot title is set to gene - probe - n=<n>, where gene is from the `fData(x)[,gene.column]`, probe is from `probes`, and <n> is the number of samples in `x`.
`gene.column`	the column name within `fData(x)` which contains the gene symbols.

nothing; a 2-panel plot is produced

Mark Cowley

if( require(lumi) ) {
  data(example.lumi)
  example.lumi
  plot_exprs_vs_detection(example.lumi, probes="oZsQEQXp9ccVIlwoQo", samples=c("A01", "A02"), 0.01, gene.column="TargetID")
}