buildXYData: XY Data Object Builder
In Glimma: Interactive HTML graphics

Common processing steps for both MA, XY and volcano plots. Expects a dataframe, table, which contains two columns labelled xlab and ylab as well as a unique identifier column labelled gene.

buildXYData(
  table,
  status,
  main,
  display.columns,
  anno,
  counts,
  xlab,
  ylab,
  status.cols,
  sample.cols,
  groups,
  transform.counts
)

`table`	dataframe containing xlab and ylab columns for plotting.
`status`	vector of length `nrow(x)` indicating the status of each gene. By default genes in the summary plot are coloured based on its differential expression status using an adjusted p-value cutoff of 5% by calling the `limma::decideTests` function, where the value of -1 marks down-regulated genes, 0 marks genes with no expression difference, and 1 marks up-regulated genes.
`main`	character string for the main title of summary plot.
`display.columns`	character vector containing names of columns from `anno` from which to display in mouseover tooltips and table.
`anno`	dataframe with `nrow(x)` rows containing gene annotations.
`counts`	numeric matrix with `nrow(x)` rows containing gene expression values. This can be used to replace raw gene counts from `dge$counts` with transformed counts e.g. logCPM or logRPKM values.
`xlab`	character string for the x-axis label of summary plot.
`ylab`	character string for the y-axis label of summary plot.
`status.cols`	vector of length 3 containing valid CSS strings for colours associated with `status` in the order of -1, 0 and 1.
`sample.cols`	character vector of length `ncol(counts)` containing valid CSS strings for colours associated with each sample to be displayed on the expression plot. If left unspecified, samples will be coloured according to `groups`.
`groups`	vector of length `ncol(dge)` representing categorisation of samples in expression plot.
`transform.counts`	the type of transform used on the counts log-cpm by default. `edgeR::cpm(counts, log=TRUE)`; defaults to FALSE.