Plot class probabilities for samples from cross-validation.

Source: R/metapredict_plot.R

Make a gtable consisting of multiple ggplots, one for each dataset used in cross-validation. Within each class, samples are sorted by the probability of the true class.

plotClassProbsCv(
  cvFit,
  lambda,
  ematMerged,
  sampleMetadata,
  className = "class",
  classLevels = NA,
  size = 1.5,
  ggplotArgs = NA
)

Arguments

cvFit

cv.glmnet object from metapredictCv().
lambda

value of lambda to use in cvFit.
ematMerged

matrix of gene expression for genes by samples.
sampleMetadata

data.frame of sample metadata.
className

column in sampleMetadata containing values of the response variable.
classLevels

Preferred order of classes.
size

Point size, passed to ggplot2::geom_point().
ggplotArgs

List of additional arguments to add to each ggplot.

Value

A ggplot object constructed by cowplot::plot_grid().