mhtplot {gap}

Manhattan plot

Description

Manhattan plot

Usage

mhtplot(data, control = mht.control(), hcontrol = hmht.control(), ...)

Arguments

data

a data frame with three columns representing chromosome, position and p values.

control

A control function named mht.control() with the following arguments:

• type a flag with value "p" or "l" indicating if points or lines are to be drawn.

• usepos a flag to use real chromosomal positions as composed to ordinal positions with default value FALSE.

• logscale a flag to indicate if p value is to be log-transformed with default value TRUE.

• base the base of the logarithm with default value 10.

• cutoffs the cut-offs where horizontal line(s) are drawn with default value NULL.

• colors the color for different chromosome(s), and random if unspecified with default values NULL.

• labels labels for the ticks on x-axis with default value NULL.

• srt degree to which labels are rotated with default value of 45.

• gap gap between chromosomes with default value NULL.

• cex cex for the data points.

• yline Margin line position.

• xline Margin line position.

hcontrol

A control function named hmht.control() with the following arguments:

• data. chunk of data to be highlighted with default value NULL.

• colors. colors for annotated genes.

• yoffset. offset above the data point showing most significant p value with default value 0.5.

• cex shrinkage factor for data points with default value 1.5.

• boxed if the label for the highlited region with default value FALSE.

...

other options in compatible with the R plot function.

Details

To generate Manhattan plot, e.g., of genomewide significance (p values) and a random variable that is uniformly distributed. By default, a log10-transformation is applied. Note that with real chromosomal positions, it is also appropriate to plot and some but not all chromosomes.

It is possible to specify options such as xlab and ylim when the plot is requested for data in other context.

Value

The plot is shown on or saved to the appropriate device.

Author(s)

Jing Hua Zhao

See Also

qqunif

Examples

## Not run: 
# foo example
test <- matrix(c(1,1,4,1,1,6,1,10,3,2,1,5,2,2,6,2,4,8),byrow=TRUE,6)
mhtplot(test)
mhtplot(test,mht.control(logscale=FALSE))

# fake example with Affy500k data
affy <-c(40220, 41400, 33801, 32334, 32056, 31470, 25835, 27457, 22864, 28501, 26273,
         24954, 19188, 15721, 14356, 15309, 11281, 14881, 6399, 12400, 7125, 6207)
CM <- cumsum(affy)
n.markers <- sum(affy)
n.chr <- length(affy)
test <- data.frame(chr=rep(1:n.chr,affy),pos=1:n.markers,p=runif(n.markers))

# to reduce size of the plot
# bitmap("mhtplot.bmp",res=72*5)
oldpar <- par()
par(cex=0.6)
colors <- rep(c("blue","green"),11)
# other colors, e.g.
# colors <- c("red","blue","green","cyan","yellow","gray","magenta","red","blue","green",
#             "cyan","yellow","gray","magenta","red","blue","green","cyan","yellow","gray",
#             "magenta","red")
mhtplot(test,control=mht.control(colors=colors),pch=19,srt=0)
title("A simulated example according to EPIC-Norfolk QCed SNPs")
axis(2)
axis(1,pos=0,labels=FALSE,tick=FALSE)
abline(0,0)
# dev.off()
par(oldpar)

mhtplot(test,control=mht.control(usepos=TRUE,colors=colors,gap=10000),pch=19,bg=colors)
title("Real positions with a gap of 10000 bp between chromosomes")
box()

png("manhattan.png",height=3600,width=6000,res=600)
opar <- par()
par(cex=0.4)
ops <- mht.control(colors=rep(c("lightgray","lightblue"),11),srt=0,yline=2.5,xline=2)
require(gap.datasets)
mhtplot(mhtdata[,c("chr","pos","p")],ops,xlab="",ylab="",srt=0)
axis(2,at=1:16)
title("An adaptable plot as .png")
par(opar)
dev.off()

data <- with(mhtdata,cbind(chr,pos,p))
glist <- c("IRS1","SPRY2","FTO","GRIK3","SNED1","HTR1A","MARCH3","WISP3","PPP1R3B",
         "RP1L1","FDFT1","SLC39A14","GFRA1","MC4R")
hdata <- subset(mhtdata,gene\
color <- rep(c("lightgray","gray"),11)
glen <- length(glist)
hcolor <- rep("red",glen)
par(las=2, xpd=TRUE, cex.axis=1.8, cex=0.4)
ops <- mht.control(colors=color,yline=1.5,xline=3,labels=paste("chr",1:22,sep=""),
                   srt=270)
hops <- hmht.control(data=hdata,colors=hcolor)
mhtplot(data,ops,hops,pch=19)
axis(2,pos=2,at=1:16)
title("Manhattan plot with genes highlighted",cex.main=1.8)

mhtplot(data,mht.control(cutoffs=c(4,6,8,16)),pch=19)
title("Another plain Manhattan plot")

# Miami plot

test <- within(test, {pr=1-p})
miamiplot(test,chr="chr",bp="pos",p="p",pr="pr")

## End(Not run)