plot.varbvs: Summarize variable selection results in a single plot.

In varbvs: Large-Scale Bayesian Variable Selection Using Variational Methods

Summarize variable selection results in a single plot.

Description

Generate a single plot that summarizes the results of fitting the Bayesian variable selection model to the data. When the variables are genetic markers, the groups are chromosomes, and the posterior probabilities are plotted on the vertical axis (typically on the logarithmic scale), the figure resembles a "Manhattan plot" typically used to summarize the results of a genome-wide association study or quantitative trait locus (QTL) mapping study.

Usage

  ## S3 method for class 'varbvs'
plot(x, score, groups, vars = NULL, var.labels,
  draw.threshold = NA, gap = 0,col = "midnightblue", pch = 20,
  scales = NULL, xlab = "variable", ylab = "posterior probability",
  main = "fitted varbvs model: variable selection results",
  abline.args = list(lty = "dotted",col = "orangered"),
  vars.xyplot.args = list(pch = 20,col = "magenta"),
  vars.ltext.args = list(col = "black",pos = 4,cex = 0.5), 
  par.settings = list(par.main.text = list(font = 1,cex = 0.8),
                      layout.heights = list(axis.top = 0, axis.bottom = 0)),
  ...)

Arguments

x	Output of function varbvs.
score	Value to plot on vertical axis. Must be a numeric vector with one entry for each variable. If missing, the posterior inclusion probability for each variable is plotted in the vertical axis, in which this probability is averaged over hyperparameter settings, treating x$logw as (unnormalized) log-marginal probabilities. As alternative, set score to the posterior inclusion probabilities that ignore correlations, using varbvsindep.
groups	Group the variables in the plot according to this argument. This must be a vector with one entry for each variable. If missing, all variables are treated as a single group. This is useful for grouping the genetic markers by chromosome in a genome-wide association study.
vars	Indices (type integer) or names (type character) of variables to highlight and label. By default, vars = NULL, meaning no variables are highlighted.
var.labels	Labels to accompany the highlighted variables only. If missing, labels are retrieved from x. If var.labels = NULL, no labels are plotted.
draw.threshold	Plot a horizontal line at this location on the vertical axis.
gap	Amount of space to leave between each group of variables in the plot.
col	Argument passed to xyplot specifying color of points.
pch	Argument passed to xyplot specifying symbol type.
scales	Argument passed to xyplot specifying how x- and y-axes are drawn.
xlab	Argument passed to xyplot specifying horizontal axis title.
ylab	Argument passed to xyplot specifying vertical axis title.
main	Argument passed to xyplot specifying main plot title.
abline.args	Additional arguments passed to panel.abline specifying how to draw the horizontal line at the location specified by draw.threshold.
vars.xyplot.args	Additional arguments passed to xyplot for drawing the highlighted variables.
vars.ltext.args	Additional arguments passed to ltext for specifying how the labels of the highlighted variables are drawn in the plot.
par.settings	Argument passed to xyplot specifying additional adjustments to the plot settings.
...	Additional arguments passed to xyplot for drawing the un-highlighted variables.

Details

Note that plot.varbvs uses function xyplot from the lattice package, and as.layer from the latticeExtra package.

Value

An object of class "trellis" generated by functions xyplot and as.layer.

Author(s)

Peter Carbonetto [e-mail]

References

P. Carbonetto and M. Stephens (2012). Scalable variational inference for Bayesian variable selection in regression, and its accuracy in genetic association studies. Bayesian Analysis 7, 73–108.

See Also

xyplot, ltext, panel.abline, varbvs, summary.varbvs, varbvsindep

varbvs documentation built on June 7, 2023, 5:43 p.m.