Using a separate dataframe to generate error bars in ggplot - r

Question

I have a data frame that looks like this:
genotype DIV3 DIV4 ...
WT 12.4 15.2
WT 35.4 35.3
HET 1.3 1.2
HET 1.5 5.2
I calculate the means and sd by the following functions:
means = aggregate(. ~ genotype, data=dat, FUN=mean)
errors = aggregate(. ~ genotype, data=dat, FUN=sd)
I am using ggplot2 to plot the means as a scatter plot. I want to use the errors dataframe for error bars, but I am having trouble calculating ymin and ymax since I have two dataframes.
Is there a better way to do this?
EDIT:
ggplot2 code:
x = melt(means)
ggplot(x_melt, aes(group=genotype, variable, value, col=genotype, shape = genotype)) +
geom_line() +
geom_point(size=3)+
theme(axis.text=element_text(size=14),
axis.title.x=element_blank(),
axis.text.x=element_text(angle = 45, vjust = 0.8, hjust = .9, color = "black"),
axis.text.y=element_text(color="black"))

Answer 1

You can do this either by creating a single dataset from the aggregate step and then reshape it before plotting.
dat2 <- do.call(`data.frame`,
aggregate(. ~genotype, dat, FUN= function(x) c(Mean=mean(x), SD=sd(x))))
nm1 <- unique(gsub("\\..*", "", colnames(dat2)[-1]))
datN <- reshape(dat2, direction="long", idvar="genotype",
varying=list(c(2,4), c(3,5)),sep=".")
datN$time <- nm1[datN$time]
colnames(datN)[3:4] <- c("Mean", "SD")
library(ggplot2)
ggplot(datN, aes(group=genotype, time, Mean, col=genotype,
shape=genotype))+
geom_line()+
geom_point(size=3)+
geom_errorbar(aes(ymin=Mean-SD, ymax=Mean+SD), width=0.1)+
theme(axis.text=element_text(size=14),
axis.title.x=element_blank(),
axis.text.x=element_text(angle = 45, vjust = 0.8, hjust = .9, color = "black"),
axis.text.y=element_text(color="black"))
Or you can merge the melted datasets means and errors
library(reshape2)
x_melt <- melt(means, value.name="Mean")
y_melt <- melt(errors, value.name="SD")
datN1 <- merge(x_melt, y_melt)
ggplot(datN1, aes(group=genotype, variable, Mean, col=genotype,
shape=genotype))+
geom_line()+
geom_point(size=3)+
geom_errorbar(aes(ymin=Mean-SD, ymax=Mean+SD), width=0.1)+
theme(axis.text=element_text(size=14),
axis.title.x=element_blank(),
axis.text.x=element_text(angle = 45, vjust = 0.8, hjust = .9, color = "black"),
axis.text.y=element_text(color="black"))
data
dat <- structure(list(genotype = c("WT", "WT", "HET", "HET"), DIV3 = c(12.4,
35.4, 1.3, 1.5), DIV4 = c(15.2, 35.3, 1.2, 5.2)), .Names = c("genotype",
"DIV3", "DIV4"), class = "data.frame", row.names = c(NA, -4L))