binPlots: Create line plots of averaged signal across a promoter
In Repitools: Epigenomic tools

Description Usage Arguments Details Value Author(s) Examples

Using a specified ordering of genes, they are split into multiple bins. In each bin, the signal across is summarized and displayed visually.

  ## S4 method for signature 'ScoresList'
binPlots(x, summarize = c("mean", "median"), ordering = NULL,
   ord.label = NULL, plot.type = c("line", "heatmap", "terrain"), n.bins = 10, cols = NULL,
   lwd = 3, lty = 1, same.scale = TRUE, symm.scale = FALSE, verbose = TRUE)

`x`	A `ScoresList` object. See `featureScores`.
`summarize`	How to summarise the scores for each bin into a single value.
`ordering`	A `data.frame` of either numeric or factor variables, with the same number of rows as the annotation used to create `x`, or a vector of such types.
`ord.label`	Character string that describes what type of data the ordering is. e.g. "log2 expression". Used to label relevant plot axis.
`plot.type`	Style of plot to draw.
`n.bins`	The number of bins to split the features into, before summarisation.
`cols`	A vector of colours to use for the bins. In order from the lowest value bin, to the highest value bin.
`lwd`	Line width of lines in line plot (either scalar or vector).
`lty`	Line type of line in line plot (either scalar or vector).
`same.scale`	Whether to keep the scale on all plots be the same.
`symm.scale`	Whether the scale on plots is symmetrical around 0.
`verbose`	Whether to print details of processing.

If plotType = "line", a line is plotted for each bin across the promoter.

If plotType = "heatmap", a series of bins are plotted as a heatmap. This can be useful to display a larger number of bins.

If plotType = "terrain", a series of bins are plotted as a 3D-terrain map. This can be useful to display a larger number of bins.

Either a single- or multiple-panel figure.

Mark Robinson

  data(chr21genes)
  data(samplesList)  # Loads 'samples.list.subset'.
  data(expr)  # Loads 'expr.subset'.

  fs <- featureScores(samples.list.subset, chr21genes, up = 5000, down = 1000, dist = "base", freq = 1000,
                      s.width = 500)
  fs@scores <- list(tables(fs)[[2]] - tables(fs)[[4]])
  names(fs) <- "PC-Norm"

  binPlots(fs, ordering = expr.subset, ord.label = "expression", plot.type = "line", n.bins = 4)
  binPlots(fs, ordering = expr.subset, ord.label = "expression", plot.type = "heatmap", n.bins = 8)