ggplot2 legend for abline and stat_smooth

Question

I have some problems with ggplot legends, here is my first code with only the legend for corrGenes, which is fine.

gene1=c(1.041,0.699,0.602,0.602,2.585,0.602,1.000,0.602,1.230,1.176,0.699,0.477,1.322)
    BIME = c(0.477,0.477,0.301,0.477,2.398,0.301,0.602,0.301,0.602,0.699,0.602,0.477,1.176)
    corrGenes=c(0.922,0.982,0.934,0.917,0.993,0.697,0.000,0.440,0.859,0.788,0.912,0.687,0.894)

DF=data.frame(gene1,BIME,corrGenes)

plot= ggplot(data=DF,aes(x=gene1,y=BIME))+
  geom_point(aes(colour=corrGenes),size=5)+
  ylab("BIME normalized counts (log10(RPKM))")+
  xlab("gene1 normalized counts (log10(RPKM))")

When I add abline and smooth, I get the correct plot with :

plot= ggplot(data=DF,aes(x=gene1,y=BIME))+
  geom_point(aes(colour=corrGenes),size=5)+
  geom_abline(intercept=0, slope=1)+
  stat_smooth(method = "lm",se=FALSE)+
  ylab("BIME normalized counts (log10(RPKM))")+
  xlab("gene1 normalized counts (log10(RPKM))")

but no way to get the legend for them, I tried and many other combinations:

plot= ggplot(data=DF,aes(x=gene1,y=BIME))+
  geom_point(aes(colour=corrGenes),size=5)+
  geom_abline(aes(colour="best"),intercept=0, slope=1)+
  stat_smooth(aes(colour="data"),method = "lm",se=FALSE)+
  scale_colour_manual(name="Fit", values=c("data"="blue", "best"="black"))+
  ylab("BIME normalized counts (log10(RPKM))")+
  xlab("gene1 normalized counts (log10(RPKM))")

If anyone has an idea to solve this tiny but very annoying problem, it would be very helpfull!

Answer 1

Finally, I found anther way using a trick. First, I've computed the linear regression and convert the results to a data frame which I add my best fit (Intercept = 0 and slope =1), then I added a column for type of data (data or best).

modele = lm(BIME ~ gene1, data=DF)
coefs = data.frame(intercept=coef(modele)[1],slope=coef(modele)[2])
coefs= rbind(coefs,list(0,1))
regression=as.factor(c('data','best'))
coefs=cbind(coefs,regression)

then I plotted it with a unique geom_abline command and moving the DF from ggplot() to geom_point() and used the linetype parameter to differenciate the two lines :

plot = ggplot()+
  geom_point(data=pointSameStrandDF,aes(x=gene1,y=BIME,colour=corrGenes),size=5)+
  geom_abline(data=coefs, aes(intercept=intercept,slope=slope,linetype=regression), show_guide=TRUE)+
  ylab("BIME normalized counts (log10(RPKM))")+
  xlab("gene1 normalized counts (log10(RPKM))")

There is maybe a way to use colors for those 2 lines, but I can't find out how?

Thanks for your help guys!

Answer 2

The show_guide=TRUE argument should display the legends for both geom_abline and stat_smooth. Try running the below code.

plot= ggplot(data=DF,aes(x=gene1,y=BIME))+
geom_point(aes(colour=corrGenes),size=5)+
geom_abline(aes(colour="best"),intercept=0, slope=1, show_guide=TRUE)+
stat_smooth(aes(colour="data"),method = "lm",se=FALSE, show_guide=TRUE)+
scale_colour_manual(name="Fit", values=c("data"="blue", "best"="black"))+
ylab("BIME normalized counts (log10(RPKM))")+
xlab("gene1 normalized counts (log10(RPKM))")