How to use custom functions in mutate (dplyr)?

Question

I'm rewriting all my code using dplyr, and need help with mutate / mutate_at function. All I need is to apply custom function to two columns in my table. Ideally, I would reference these columns by their indices, but now I can't make it work even referencing by names.

The function is:

binom.test.p <- function(x) {
  if (is.na(x[1])|is.na(x[2])|(x[1]+x[2])<10) {
    return(NA)
  } 
  else {
    return(binom.test(x, alternative="two.sided")$p.value)
  }
} 

My data:

table <- data.frame(geneId=c("a", "b", "c", "d"), ref_SG1_E2_1_R1_Sum = c(10,20,10,15), alt_SG1_E2_1_R1_Sum = c(10,20,10,15))

So I do:

table %>%
  mutate(Ratio=binom.test.p(c(ref_SG1_E2_1_R1_Sum, alt_SG1_E2_1_R1_Sum)))
Error: incorrect length of 'x'

If I do:

table %>% 
mutate(Ratio=binom.test.p(ref_SG1_E2_1_R1_Sum, alt_SG1_E2_1_R1_Sum))
Error: unused argument (c(10, 20, 10, 15))

The second error is probably because my function needs one vector and gets two parameters instead.

But even forgetting about my function. This works:

table %>%
  mutate(sum = ref_SG1_E2_1_R1_Sum + alt_SG1_E2_1_R1_Sum)

This doesn't:

    table %>%
      mutate(.cols=c(2:3), .funs=funs(sum=sum(.)))
Error: wrong result size (2), expected 4 or 1

So it's probably my misunderstanding of how dplyr works.

Answer 1

Your problem seems to be binom.test instead of dplyr, binom.test is not vectorized, so you can not expect it work on vectors; You can use mapply on the two columns with mutate:

table %>% 
    mutate(Ratio = mapply(function(x, y) binom.test.p(c(x,y)), 
                          ref_SG1_E2_1_R1_Sum, 
                          alt_SG1_E2_1_R1_Sum))

#  geneId ref_SG1_E2_1_R1_Sum alt_SG1_E2_1_R1_Sum Ratio
#1      a                  10                  10     1
#2      b                  20                  20     1
#3      c                  10                  10     1
#4      d                  15                  15     1

---

As for the last one, you need mutate_at instead of mutate:

table %>%
      mutate_at(.vars=c(2:3), .funs=funs(sum=sum(.)))