在 dplyr 中的 group_by 之后应用 p.adjust 函数

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

@zesla your code is fine. Your confusion lies in the difference between family-wise error rate and false discovery rate which is what BH does. With BH you are much more likely to see those equal values.

If you look at the doco for p.adjust and run the sample code:

set.seed(123)
x <- rnorm(50, mean = c(rep(0, 25), rep(3, 25)))
p <- 2*pnorm(sort(-abs(x)))

round(p, 3)
round(p.adjust(p), 3)
round(p.adjust(p, "BH"), 3)

you'll see the same effect. You can also run a traditional family-wise error rate adjustment like Holm to see the effect on your own data...

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

See also this article on how BH is calculated

Answer 2

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