plotManhattan: plot Manhattan-like plots

In BayesSUR: Bayesian Seemingly Unrelated Regression

plot Manhattan-like plots

Description

Plot Manhattan-like plots for marginal posterior inclusion probabilities (mPIP) and numbers of responses of association for predictors of a BayesSUR class object.

Usage

plotManhattan(
  x,
  manhattan = c("mPIP", "numResponse"),
  x.loc = FALSE,
  axis.label = "auto",
  mark.responses = NULL,
  xlab1 = "Predictors",
  ylab1 = "mPIP",
  xlab2 = "Predictors",
  ylab2 = "No. of responses",
  threshold = 0.5,
  las = 0,
  cex.axis = 1,
  mark.pos = c(0, 0),
  mark.color = 2,
  mark.cex = 0.8,
  header = "",
  ...
)

Arguments

x	an object of class BayesSUR
manhattan	value(s) in c('mPIP', 'numResponse'). manhattan='mPIP' shows the Manhattan-like plot of the marginal posterior inclusion probabilities (mPIP). manhattan='numResponse' shows the Manhattan-like plot of the number of responses. The default is to show both figures.
x.loc	a vector of features distance
axis.label	a vector of predictor names which are shown in the Manhattan-like plot. The value "NULL" only showing the indices. The default "auto" show the predictor names from the original data.
mark.responses	a vector of response names which are shown in the Manhattan-like plot for the mPIP
xlab1	a title for the x axis of Manhattan-like plot for the mPIP
ylab1	a title for the y axis of Manhattan-like plot for the mPIP
xlab2	a title for the x axis of Manhattan-like plot for the numbers of responses
ylab2	a title for the y axis of Manhattan-like plot for the numbers of responses
threshold	threshold for showing number of response variables significantly associated with each feature
las	graphical parameter of plot.default
cex.axis	graphical parameter of plot.default
mark.pos	the location of the marked text relative to the point
mark.color	the color of the marked text. The default color is red.
mark.cex	the fontsize of the marked text. The default fontsize is 0.8
header	the main title
...	other arguments

Examples

data("exampleEQTL", package = "BayesSUR")
hyperpar <- list(a_w = 2, b_w = 5)

set.seed(9173)
fit <- BayesSUR(
  Y = exampleEQTL[["blockList"]][[1]],
  X = exampleEQTL[["blockList"]][[2]],
  data = exampleEQTL[["data"]], outFilePath = tempdir(),
  nIter = 10, burnin = 0, nChains = 1, gammaPrior = "hotspot",
  hyperpar = hyperpar, tmpFolder = "tmp/"
)

## check output
# show the Manhattan-like plots
plotManhattan(fit)

BayesSUR documentation built on Aug. 28, 2023, 5:09 p.m.