apply p.adjust function after group_by in dplyr

Question

My data dat is like this

set.seed(123)        
dat<- data.frame(
                comp = rep(1:4,2),
                grp = rep(c('A','B'), each=4),
                pval = runif(8, min=0, max=0.1) )
dat$pval[sample(nrow(dat), 1)] <- NA

pval column contains a list of p values from multiple ttest within each large group.
Now I need to apply the base r function p.adjust to adjust the p values within each group (A,B,...) what I did was:

dat %>%
    group_by(grp) %>% 
    mutate(pval.adj = p.adjust (pval, method='BH'))

Below is the output of the above code:

comp grp  pval       pval.adj
1   A   0.02875775  0.08179538  
2   A   0.07883051  0.08830174  
3   A   0.04089769  0.08179538  
4   A   0.08830174  0.08830174  
1   B   NA  NA  
2   B   0.00455565  0.01366695  
3   B   0.05281055  0.07921582  
4   B   0.08924190  0.08924190  

The result does not make sense. The last entry of each group, pval and pval.adj are equal. Some pval.adj are much closer to pval than others. I think something is wrong with applying the p.adjust function after group_by. It took me hours but could not figure out why... I appreciate if someone could help me with that.

below is the p.adjust function usage:

p.adjust(p, method = p.adjust.methods, n = length(p))
p.adjust.methods
# c("holm", "hochberg", "hommel", "bonferroni", "BH", "BY",
#   "fdr", "none")

Answer 1

you are calling p.adjust on each P value independently. I usually call p.adjust outside of the pipe for this reason.