sequenza (version 2.1.2)

cp.plot: Plot log-posterior probability for the tested values of cellularity and ploidy

Description

This function uses the colorgram function from the package squash to plot log-posterior probability for the tested combinations of cellularity and ploidy

Usage

cp.plot(cp.table, xlab = "Ploidy", ylab = "Cellularity",
           zlab = "Scaled rank LPP", 
           colFn = colorRampPalette(c('white', 'lightblue')), ...)
   cp.plot.contours(cp.table, likThresh = c(0.95), alternative = TRUE,
                    col = palette(), legend.pos = "bottomright", pch = 18,
                    alt.pch = 3, ...)

Arguments

cp.table

list, as output from baf.model.fit or mufreq.model.fit.

xlab

xlab parameter as in the function colorgram.

ylab

ylab parameter as in the function colorgram.

zlab

zlab parameter as in the function colorgram.

colFn

colFn parameter as in the function colorgram.

likThresh

vector of quantiles to define tresholds for the confindent regions.

alternative

boolean parameter, if TRUE the alternative solutions are computed and plotted.

col

vector of colors.

legend.pos

position for placing the legend.

pch

character used to indicate the point estimate.

alt.pch

if alternative is set to TRUE defines the character to indicate alternative solutions.

...

additional arguments accepted by the function colorgram for cp.plot, or contour for cp.plot.contours.

Examples

# NOT RUN {
data(CP.example)
cp.plot(CP.example)
cp.plot.contours(CP.example, add = TRUE)

cp.plot(CP.example)
cp.plot.contours(CP.example, likThresh = c(0.95, 0.9999), add = TRUE)
# }