plot.clonal.models: Visualize clonal evolution models using various plots.
In hdng/clonevol: Clonal ordering and visualization

Description Usage Arguments Examples

Plot evolution models and clonal admixtures inferred by infer.clonal.models function using various plots, including: bell plots, sphere of cells, node-based and branch-based clonal evolution trees.

1	plot.clonal.models(x, out.prefix, ...)

`x:`	output of infer.clonal.models function
`out.dir:`	output directory for the plots
`models.to.plot:`	row numbers of the models to plot in x$matched$index
`scale.monoclonal.cell.frac:`	c(TRUE, FALSE); if TRUE, scale cellular fraction in the plots (ie. cell fraction will be scaled by 1/purity = 1/max(VAF*2)), default = TRUE
`width:`	width of the plots (in), if NULL, automatically choose width
`height:`	height of the plots (in), if NULL, automatically choose height
`out.format:`	format of the plot files ('png', 'pdf', 'pdf.multi.files')
`resolution:`	resolution of the PNG plot file
`overwrite.output:`	if TRUE, overwrite output directory, default=FALSE
`max.num.models.to.plot:`	max number of models to plot; default = 10
`individual.sample.tree.plot:`	c(TRUE, FALSE); plot individual sample trees if TRUE, combined graph that preserved sample labels will be produced in graphml output, default = FALSE
`merged.tree.plot:`	Also plot the merged clonal evolution tree across samples
`merged.tree.node.annotation:`	the name of the column in x$matched$mereged.trees[[i]] that will be used to annotate the clones in trees see also parameter node.annotation of function plot.tree default = 'sample.with.nonzero.cell.frac.ci'
`merged.tree.cell.frac.ci:`	Show cell fraction CI for samples in merged tree
`tree.node.label.split.character:`	sometimes the labels of samples are long, so to display nicely many samples annotated at leaf nodes, this parameter specify the character that splits sample names in merged clonal evolution tree, so it will be replaced by line feed to display each sample in a line,
`tree.node.num.samples.per.line:`	Number of samples displayed on each line in the tree node; default NULL (do not attempt to distribute samples on lines)
`trimmed.tree.plot:`	Also plot the trimmed clonal evolution trees across samples in a separate PDF file
`color.node.by.sample.group:`	color clones by grouping found in sample.group. based on the grouping, clone will be stratified into different groups according to what sample group has the clone signature variants detected. This is useful when analyzing primary, metastasis, etc. samples and we want to color the clones based on if it is primary only, metastasis only, or shared, etc. etc.
`merged.tree.node.size.scale:`	scale merged tree node size by this value, compared to individual tree node size
`merged.tree.node.text.size.scale:`	scale merged tree node text size by this value, compared to individual tree text size
`clone.time.step.scale:`	scaling factor for distance between the tips of the polygon/bell representing clone
`zero.cell.frac.clone.color:`	color clone with zero cell fraction in the sample with this color (default = NULL, color using matching color
`zero.cell.frac.clone.border.color:`	border color of the bell for clones that are not found in sample; if equal "fill", the fill color of bell is used auto-generated)
`cell.frac.ci:`	Display cell frac CI
`disable.cell.frac:`	Completely remove cell frac CI info. in plots
`samples:`	samples to plot (ordered), equal vaf.col.names used in infer.clonal.models
`bell.border.width:`	border with of bell curve
`merged.tree.clone.as.branch:`	default=TRUE, plot merged.tree with branch as clone (mtcab)
`mtcab.angle:`	mtcab branch angle in degree
`mtcab.branch.width:`	mtcab branch witdh in points
`mtcab.branch.text.size:`	mtcab branch text size (cex)
`mtcab.node.size=3:`	mtcab node size
`mtcab.node.label.size:`	mtcab node label text size
`mtcab.node.text.size:`	mtcab node annotation text size
`mtcab.event.sep.char:`	mtcab event separator (used to break down eventa
`mtcab.show.event:`	show mapped events on branches to multiple lines)
`mtcab.tree.rotation.angle:`	c(0 - bottom up, 90 - left to right, 180 - top down); angle to rotate the tree, default = 180
`mtcab.tree.text.angle:`	text angle, if NULL auto-determine
`xstarts:`	sample-named vector of x axis start positions of the samples which will be used to layout sample bell plots over clinical timeline
`xstops:`	sample-named vector of x axis stop positions of the samples
`fancy.variant.boxplot.*:`	map to corresponding params of variant.box.plot
`merged.tree.distance.from.bottom:`	distance from the plot area for the merged tree (inches). If the height of combined final plot is large, increase this to make sure the tree is not stretched vertically
`panel.widths:`	vector of widths of the panels to plot which will be used to scale the widths of variant boxplot, bell plot, and tree against each other
`trimmed.merged.tree.plot:`	plot trimmed merged tree (T/F, default=T)
`trimmed.merged.tree.plot.width:`	width (inches)
`trimmed.merged.tree.plot.height:`	height (inches)

data(aml1)
y = aml1
## Not run: 
plot.clonal.models(y,
                 box.plot = TRUE,
                 fancy.boxplot = TRUE,
                 fancy.variant.boxplot.highlight = 'is.driver',
                 fancy.variant.boxplot.highlight.shape = 21,
                 fancy.variant.boxplot.highlight.fill.color = 'red',
                 fancy.variant.boxplot.highlight.color = 'black',
                 fancy.variant.boxplot.highlight.note.col.name = 'gene',
                 fancy.variant.boxplot.highlight.note.color = 'blue',
                 fancy.variant.boxplot.highlight.note.size = 2,
                 fancy.variant.boxplot.jitter.alpha = 1,
                 fancy.variant.boxplot.jitter.center.color = 'grey50',
                 fancy.variant.boxplot.base_size = 12,
                 fancy.variant.boxplot.plot.margin = 1,
                 fancy.variant.boxplot.vaf.suffix = '.VAF',
                 clone.shape = 'bell',
                 bell.event = TRUE,
                 bell.event.label.color = 'blue',
                 bell.event.label.angle = 60,
                 clone.time.step.scale = 1,
                 bell.curve.step = 2,
                 merged.tree.plot = TRUE,
                 tree.node.label.split.character = NULL,
                 tree.node.shape = 'circle',
                 tree.node.size = 30,
                 tree.node.text.size = 0.5,
                 merged.tree.node.size.scale = 1.25,
                 merged.tree.node.text.size.scale = 2.5,
                 merged.tree.cell.frac.ci = FALSE,
                 merged.tree.clone.as.branch = TRUE,
                 mtcab.event.sep.char = ',',
                 mtcab.branch.text.size = 1,
                 mtcab.branch.width = 0.75,
                 mtcab.node.size = 3,
                 mtcab.node.label.size = 1,
                 mtcab.node.text.size = 1.5,
                 cell.plot = TRUE,
                 num.cells = 100,
                 cell.border.size = 0.25,
                 cell.border.color = 'black',
                 clone.grouping = 'horizontal',
                 scale.monoclonal.cell.frac = TRUE,
                 show.score = FALSE,
                 cell.frac.ci = TRUE,
                 disable.cell.frac = FALSE,
                 out.dir = '/tmp',
                 out.format = 'pdf',
                 overwrite.output = TRUE,
                 width = 8,
                 height = 4,
                 panel.widths = c(3,4,2,4,2))

## End(Not run)