sym.plot: Sym Plot
In dieterich-lab/CellPlot: Segmented Bar Chart Plot Methods

Description Usage Arguments Author(s) Examples

Plots a split barchart, showing the proportions of two mutually exclusive sets in relation to a set containing them both. E.g., Gene Ontology terms, showing the proportions of differentially down-regulated and up-regulated annotated genes from a perturbation experiment. The color of the central column elements maps to the value provided in x (e.g. GO term enrichment). Associated genes may be provided as a list of vectors of expression values, same as for cell.plot(), or as separate vectors x.up and x.down, providing the numbers of up- and down-regulated genes in the same order as x.

sym.plot(x, cells = NULL, x.annotated, x.up = NULL, x.down = NULL,
  x.col = NULL, sort = F, main = "", elem.bounds = NULL,
  x.mar = c(0.2, 0), y.mar = c(0.2, 0), bar.lwd = 2, bar.scale = NULL,
  space = 0.1, mid.gap = 0.1, mid.bounds = NULL, mid.col = c("white",
  "darkred"), key.lab = "GO Term Enrichment", key.n = 11,
  cols = c("deepskyblue2", "coral"), group.labels = c("Downregulated",
  "Annotated", "Upregulated"), group.cex = 0.8, axis.cex = 0.8,
  mid.cex = 0.8, lab.cex = 1, ticksize = 10, x.bound = NULL, ...)

`x`	Strictly positive numeric vector.
`cells`	List of vectors (e.g. gene logfold-changes). Must be the same length and order as x.
`x.annotated`	Cardinality of each functional set (e.g. total number of genes annotated in a given GO term). Must be the same length and order as x.
`x.up`	Vector containing numbers of up-regulated genes in each functional set. Must be the same length and order as x. Overridden by the cells parameter, if provided.
`x.down`	Vector containing numbers of down-regulated genes in each functional set. See x.up.
`x.col`	Vector of color names. Must be the same length as x. Defaults to black.
`sort`	Sort categories by their cardinality. Defaults to FALSE.
`main`	Title.
`elem.bounds`	Vector of length 2 specifying a filter on minimum and maximum number of elements in both categories combined. Defaults to NULL, in which case no filter is applied.
`x.mar`	Left and right margins as fractions of plot width. Defaults to c(0.2,0.05).
`y.mar`	Top and bottom margins as fractions of plot height. Defaults to c(0.1,0).
`bar.lwd`	Line width of bar elements. Defaults to 2.
`bar.scale`	If not NULL (the default), set bar height to a fixed value relative to the numeric factor provided. Use to ensure consistency across plots with varying numbers of elements.
`space`	Free space above and below bars as a fraction of bar height. Defaults to 0.1.
`mid.gap`	Free space left between the extremes of the central column and the bar elements, as a fraction of central column width. Defaults to 0.1.
`mid.bounds`	Lower and upper bound on the color scale mapping of the central column (i.e. mapping of x). Defaults to c(0, max(x)).
`mid.col`	Color scale for mapping of x to the central column elements. Defaults to c("white","darkred").
`key.lab`	Label for color key.
`key.n`	Number of legend boxes for the color key. Defaults to 11.
`cols`	Colors for left and right bars. Defaults to c("deepskyblue2","coral").
`group.labels`	Labels for left bars, central column, and right bars. Defaults to c("Downregulated","Annotated","Upregulated").
`group.cex`	Scaling factor for group labels. Defaults to 0.8.
`axis.cex`	Scaling factor for axis labeling. Defaults to 0.8.
`mid.cex`	Scaling factor for central column labeling. Defaults to 0.8.
`lab.cex`	Scaling factor for functional group labels. Defaults to 1.
`ticksize`	Spacing between x-axis ticks. Defaults to 10.
`x.bound`	x.bound Numeric, must be positive and <= 100. Specifies upper bound of x-axis scale (in percent). If NULL (the default), this value is chosen automatically.
`...`	Other arguments, ignored.

Robert Sehlke [aut]
Sven E. Templer [ctb]

## Not run: 

### Random data example

# Generate random positive vector and name it
x = sort( runif(16, min = 1, max = 3), decreasing = T )
names(x) = paste("GO Term",1:16)

# Label colors
xcolor = c(rep("darkslategrey",4), rep("chartreuse4",4), rep("coral4",8))

# Generate list with random vectors, one for each entry in x
cells = list()
xc = round( runif(16, min=21, max=100) )
for (i in 1:length(xc)) { cells = c(cells, list(runif(xc[i],-5,5))) }
cells[[9]][1:2] = Inf
cells[[9]][3] = -Inf
cells.annotated <- sapply(cells, length)

# Plot with spacers
sym.plot( x, cells, cells.annotated, 
          xcolor, spacers = c(4,8), xlab.ticks = 5, cell.limit = 80,
          main="Cell Plot Demo", xlab="log(enrichment)" )
  
### golub.deg data example

data(golubstat)
x <- subset(golubstat, p<=.05 & significant>4 & !duplicated(genes))
x <- head(x, 10)
sym.plot( x = setNames(x$loge, x$term), cells = x$deg.log2fc, x.annotated = x$annotated,
          main = "Golub et al. (1999) - Gene Ontology Enrichment" )

## End(Not run)