plotStabilityPaths: Plot Stability Paths

In fmicompbio/monaLisa: Binned Motif Enrichment Analysis and Visualization

Plot Stability Paths

Description

Plot the stability paths of each variable (predictor), showing the selection probability as a function of the regularization step.

Usage

plotStabilityPaths(
  se,
  selProbMin = metadata(se)$stabsel.params.cutoff,
  selColor = "cadetblue",
  notSelColor = "grey",
  selProbCutoffColor = "firebrick",
  linewidth = 0.5,
  alpha = 1,
  ylim = c(0, 1),
  labelPaths = FALSE,
  labels = NULL,
  labelNudgeX = 8,
  labelSize = 3
)

Arguments

se	The SummarizedExperiment object resulting from stability selection, by running randLassoStabSel.
selProbMin	A numerical scalar in [0,1]. Predictors with a selection probability greater than selProbMin are shown as colored lines. The color is defined by the col argument.
selColor	Color for the selected predictors which have a selection probability greater than selProbMin.
notSelColor	Color for the rest of the (un-selected) predictors.
selProbCutoffColor	Color for the line depicting the selection probability cutoff.
linewidth	Line width.
alpha	Line transparency of the stability paths.
ylim	Limits for y-axis.
labelPaths	If TRUE, the predictor labels will be shown at the end of the stability paths. The predictor labels given in labels will be shown. If unspecified, the labels corresponding to the selected predictors will be added. If predictors have the same y-value in the last regularization step, the labels will be shown in a random order. One needs to use set.seed to reproduce the plot in this case.
labels	If labelPaths = TRUE, the predictors which should be labelled. If NULL, the selected predictors greater than metadata(se)$stabsel.params.cutoff will be shown.
labelNudgeX	If labelPaths = TRUE, how much to nudge the labels to the right of the x-axis.
labelSize	If labelPaths = TRUE, the size of the labels.

Value

a ggplot2 object.

See Also

stabsel

Examples

## create data set
Y <- rnorm(n = 500, mean = 2, sd = 1)
X <- matrix(data = NA, nrow = length(Y), ncol = 50)
for (i in seq_len(ncol(X))) {
  X[ ,i] <- runif(n = 500, min = 0, max = 3)
}
s_cols <- sample(x = seq_len(ncol(X)), size = 10,
  replace = FALSE)
for (i in seq_along(s_cols)) {
  X[ ,s_cols[i]] <- X[ ,s_cols[i]] + Y
}

## reproducible randLassoStabSel() with 1 core
set.seed(123)
ss <- randLassoStabSel(x = X, y = Y)
plotStabilityPaths(ss)

fmicompbio/monaLisa documentation built on June 15, 2025, 1:50 p.m.