clonevol (version 0.99.11)

plot.clonal.models: Visualize clonal evolution models using various plots.

Description

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.

Usage

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

Arguments

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)

Examples

# NOT RUN {
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))
# }
# NOT RUN {
# }