I would like to add the p.value of the Spearman's correlation test on my ggplot.
I have a data frame, Global.log.CD8.Density:
head(Global.log.CD8.Density)
ID Global.log.CD8.Density Signature Weight
IM_186 0.124566 s1 0.56427854
IM_152 5.041160 s1 0.28232970
IM_172 1.385508 s1 0.20986138
IM_148 6.067057 s1 0.42067503
IM_146 2.278153 s1 0.23883911
IM_174 5.481756 s1 0.05284056
There are 7 Signatures
, s1-s7, for each ID
with different Weight
values. I have created a facet dot plot to show the correlation between Global.log.CD8.Density
and Weight
for each Signature
, and displayed the p.value using the following code:
ggplot(Global.log.CD8.Density,
mapping = aes(x=Weight, y=Global.log.CD8.Density))+
geom_point(aes(colour=Signature))+
facet_wrap(~Signature, nrow = 2)+
geom_smooth(method = "lm", se = F) +
stat_fit_glance(method = 'lm',
method.args = list(formula = y~x),
geom = 'text',
aes(label = paste( "italic (p)== ", signif(..p.value.., digits = 4))),
label.x.npc = "right", label.y.npc = 0.10,
size = 3, parse=TRUE)
This pastes the p.value of the Pearson's correlation. I would like to know if there is a way to modify the code to display the Spearman's correlation instead. I know you can do the following code to get the result:
Global.CD8.spearman <- Global.log.CD8.Density %>%
group_by(Signature) %>%
do(tidy(cor.test(.$Weight, .$Global.log.CD8.Density, method='spearman')))
ggplot(Global.log.CD8.Density, aes(Weight,Global.log.CD8.Density))+
geom_point(aes(colour=Signature))+
facet_wrap(~Signature, nrow = 2)+
geom_smooth(method = "lm", se = F) +
geom_text (data=Global.CD8.spearman,
aes(0.55,0.55,label = ifelse(p.value>0.05,paste( "italic (p)== ",
signif(p.value, digits = 2)),"italic (p)<0.05")),
size = 3, parse=TRUE)
but I was wondering if there is a way to modify stat_fit_glance
or any other ggpmisc
tool to get that result.
Many thanks