| mhtplot.trunc {gap} | R Documentation |
To generate truncated Manhattan plot, e.g., of genomewide significance (P values) or a random variable that is uniformly distributed.
mhtplot.trunc(x, chr = "CHR", bp = "BP", p = "P", snp = "SNP", z = NULL,
col = c("gray10", "gray60"),
chrlabs = NULL, suggestiveline = -log10(1e-05),
genomewideline = -log10(5e-08), highlight = NULL, logp = TRUE,
annotatePval = NULL, annotateTop = TRUE, cex.mtext=0.6, cex.text=0.8,
mtext.line=2, cex.y= 1, y.ax.space=5, y.brk1, y.brk2, ...)
x |
A data.frame |
chr |
Chromosome |
bp |
Position |
p |
P value |
snp |
SNP |
z |
Z-score, i.e., BETA/SE with extremely small P |
col |
Colours |
chrlabs |
Chromosome labels |
suggestiveline |
Suggestive line |
genomewideline |
Genomewide line |
highlight |
Highlight |
logp |
log(P) |
annotatePval |
Annotate P |
annotateTop |
Annotate top |
cex.mtext |
axis label size |
cex.text |
SNP label font |
mtext.line |
position of the y lab |
cex.y |
y axis numbers |
y.ax.space |
y.ax.space |
y.brk1 |
y.brk1 |
y.brk2 |
y.brk2 |
... |
other options |
The plot is shown on or saved to the appropriate device.
James Peters
## Not run:
#
require(gap.datasets)
mhtplot.trunc(mhtdata,chr = "chr", bp = "pos", p = "p", snp = "rsn", y.brk1=10, y.brk2=12)
# https://portals.broadinstitute.org/collaboration/
# giant/images/0/0f/Meta-analysis_Locke_et_al+UKBiobank_2018.txt.gz
gz <- gzfile("Meta-analysis_Locke_et_al+UKBiobank_2018_UPDATED.txt.gz")
BMI <- within(read.delim(gz,as.is=TRUE), {Z <- BETA/SE})
library(Rmpfr)
within(subset(BMI, P==0), {P <- format(2*pnorm(mpfr(abs(BETA/SE),100),lower.tail=FALSE))})
png("BMI.png", res=300, units="in", width=9, height=6)
par(oma=c(0,0,0,0), mar=c(5,6.5,1,1))
mhtplot.trunc(BMI, chr="CHR", bp="POS", p="P", snp="SNP", z = "Z",
suggestiveline=FALSE, genomewideline=-log10(1e-8), logp = TRUE,
cex.mtext=0.6, cex.text=0.7,
mtext.line=4, y.brk1=200, y.brk2=280, cex.axis=0.6, cex.y=0.6, cex=0.5,
y.ax.space=20,
col = c("blue4", "skyblue")
)
dev.off()
## End(Not run)