This function plots the selection probabilities of predictors (for example the selected motifs), optionally multiplied with either +1 or -1 to give a sense of both the strength and the directionality of the associated effects. The directionality is estimated from the sign of the correlation coefficient between each predictor and the response vector.
The SummarizedExperiment
object with the results from
stability selection (typically returned by randLassoStabSel
).
A logical scalar. If TRUE
, selection probabilities
are plotted with the sign of the marginal correlation between a predictor
and the response.
A numerical scalar in [0,1]. Predictors with a selection
probability greater than selProbMin
are shown as colored bars. The
color is defined by col[1]
. By default, selProbMin
is
extracted from the parameters stored in se
.
A numerical scalar in [0,1] less than
selProbMin
.
Predictors with a selection probability greater than selProbMinPlot
but less than selProbMin
are shown as bars with color col[2]
.
selProbMinPlot
is useful to include additional predictors in the
plot that were not selected according to selProbMin
but may be
close to that cutoff. Setting selProbMinPlot = 0
will create a plot
including all predictors.
A logical scalar. If TRUE
, the value of
selProbMin
is shown by a horizontal dashed line of color
col[3]
.
A color vector giving the three colors used for predictors with
selection probability greater than selProbMin
, additional predictors
with selection probability greater than selProbMinPlot
, and the
selection probability cutoff line.
A character scalar with the correlation method to use in the
calculation of predictor-response marginal correlations. One of "pearson",
"kendall" or "spearman" (see cor
).
A numeric scalar defining how much the y axis limits should be expanded beyond the plotted probabilities to allow for space for the bar labels.
the position of the legend in the bar plot (will
be passed to legend(x=legend)
to control legend position).
A scalar that controls the text size in the legend relative
to the current par("cex")
(see legend
).
additional parameters passed to barplot
.
a matrix
with one column, containing the coordinates of the
bar midpoints, or NULL
if no bar plot is drawn.
This function creates a bar plot using the
barplot
function.
Each bar corresponds to a predictor (motif) and the colors correspond to
whether or not it was selected. The y-axis shows the selection
probabilities (directional=FALSE
) or selection probabilities with
the sign of the marginal correlation to the response
(directional=TRUE
).
## 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)
plotSelectionProb(ss)