MKmisc (version 1.9)

transformations: New Transformations for Use with ggplot2 Package

Description

The functions generate new transformations for the generalized logarithm and the negative logarithm that can be used for transforming the axes in ggplot2 plots.

Usage

glog_trans(base = exp(1))
glog10_trans()
glog2_trans()
scale_y_glog(...)
scale_x_glog(...)
scale_y_glog10(...)
scale_x_glog10(...)
scale_y_glog2(...)
scale_x_glog2(...)
neglog_breaks(n = 5, base = 10)
neglog_trans(base = exp(1))
neglog10_trans()
neglog2_trans()
scale_y_neglog(...)
scale_x_neglog(...)
scale_y_neglog10(...)
scale_x_neglog10(...)
scale_y_neglog2(...)
scale_x_neglog2(...)

Value

A transformation.

Arguments

base

a positive or a positive or complex number: the base with respect to which generalized and negative logarithms are computed. Defaults to e=exp(1).

...

Arguments passed on to scale_(x|y)_continuous.

n

desired number of breaks.

Author

Matthias Kohl

Details

The functions can be used to transform axes in ggplot2 plots. The implementation is analogous to e.g. scale_y_log10.

The negative logarithm is for instance of use in case of p values (e.g. volcano plots),

The functions were adapted from packages scales and ggplot2.

References

H. Wickham. ggplot2: Elegant Graphics for Data Analysis. Springer-Verlag New York, 2016.

See Also

scale_continuous, log_trans

Examples

library(ggplot2)
data(mpg)
p1 <- ggplot(mpg, aes(displ, hwy)) + geom_point()
p1
p1 + scale_x_log10()
p1 + scale_x_glog10()
p1 + scale_y_log10()
p1 + scale_y_glog10()

## A volcano plot
x <- matrix(rnorm(1000, mean = 10), nrow = 10)
g1 <- rep("control", 10)
y1 <- matrix(rnorm(500, mean = 11.25), nrow = 10)
y2 <- matrix(rnorm(500, mean = 9.75), nrow = 10)
g2 <- rep("treatment", 10)
group <- factor(c(g1, g2))
Data <- rbind(x, cbind(y1, y2))
pvals <- apply(Data, 2, function(x, group) t.test(x ~ group)$p.value,
               group = group)
## compute log-fold change
logfc <- function(x, group){
  res <- tapply(x, group, mean)
  log2(res[1]/res[2])
}
lfcs <- apply(Data, 2, logfc, group = group)
ps <- data.frame(pvals = pvals, logfc = lfcs)
ggplot(ps, aes(x = logfc, y = pvals)) + geom_point() +
    geom_hline(yintercept = 0.05) + scale_y_neglog10() +
    geom_vline(xintercept = c(-0.1, 0.1)) + xlab("log-fold change") +
    ylab("-log10(p value)") + ggtitle("A Volcano Plot")