plotManhattan {BayesSUR}R Documentation

plot Manhattan-like plots for marginal posterior inclusion probabilities (mPIP) and numbers of responses of association for predictors

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,
  which = c(1, 2),
  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

which

if it's value "1" showing the Manhattan-like plot of the marginal posterior inclusion probabilities (mPIP). If it's value "2" showing 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 orginal 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 = 100, burnin = 50, nChains = 2, gammaPrior = "hotspot",
                hyperpar = hyperpar, tmpFolder = "tmp/" )

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


[Package BayesSUR version 2.0-1 Index]