Description Usage Arguments Details Value Author(s) References Examples
This function plot a list of adjusted p-values against the index of the entries ranked ascendingly by their p-value. This allows assesing how the distributions of p-values compare between different studies or against a meta-analysis.
1 2 |
pvals |
A (named) list containing two data.frames or arrays with two columns. The first columns contains the raw p-values and the second one the adjusted ones. |
s.legend |
The names of the studies (used in the plot legend). Either this or names
of |
colos |
Colors to be used for the plotting. If less than 12 studies are given in
|
ylim |
Limits for plotting the y-axis (Must be between 0 and 1). |
log |
Which axis should be printed log scaled. Either ('y' (default),'x','xy' or ”) |
plot.title |
The plot title. |
zero.sub |
Replacemetn for 0s. |
legend.pos |
Position of the legend. |
lty |
Line with passed to |
lwd |
Line type passed to |
A graphical representation of studie p-values and meta-analysis results as given in Rhodes et al. 2002.
If you have a named list and s.legend
set, the later parameter
will be used in the legend plot.
Having log
set to y
or xy
and the y-axis including 0, this
will result in an error.
In case you want to print the study raw p-values against their rank, just have the second column contain the values from the first one.
A plot
Karl Kugler <karl@eigenlab.net>
Rhodes, D. R., (2002). Meta-analysis of microarrays: interstudy validation of gene expression profiles reveals pathway dysregulation in prostate cancer. Cancer research, 62(15), 4427-33.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 | pvals <- lapply(1:11, function(i){runif(1000)})
set.seed(12345)
pvals <- lapply(1:11, function(i){pnorm(rnorm(1000, sd=sample(c(1,1.2,1.4),1)), lower=TRUE)})
pvals <- lapply(pvals, function(x){cbind(x, p.adjust(x,method="BH"))})
names(pvals) <- paste("study",1:11)
plotPvsRank(pvals, lwd=2, lty=1)
##make line for last study look different
plotPvsRank(pvals, lwd=c(rep(1,10),2), lty=c(rep(1,10),2))
#log scale only x
plotPvsRank(pvals, log="x", lwd=2, lty=1)
#inverse y, place legend at the bottom, and add title
plotPvsRank(pvals, log="y", ylim=c(0.0001,1),lwd=2, lty=1,
legend.pos="bottomright", plot.title="my title")
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