t-test of triplicates in a horizontal data frame

I am trying to make a loop, so I can test multiple conditions: cond_A, cond_B and cond_C, each against the same control ('ctrl'). Each condition and control is represented by a triplicate. As outcome I would like to get a dataframe with condition names and pvalues.

Here is my input:

structure(list(ctrl_1 = 1L, ctrl_2 = 2L, ctrl_3 = 3L, cond_A_1 = 4L, 
    cond_A_2 = 4L, cond_A_3 = 4L, cond_B_1 = 5L, cond_B_2 = 5L, 
    cond_B_3 = 7L, cond_C_1 = 8L, cond_C_2 = 9L, cond_C_3 = 2L), .Names = c("ctrl_1", 
"ctrl_2", "ctrl_3", "cond_A_1", "cond_A_2", "cond_A_3", "cond_B_1", 
"cond_B_2", "cond_B_3", "cond_C_1", "cond_C_2", "cond_C_3"), class = "data.frame", row.names = c(NA, 
-1L))

And expected output with hypothetical pvalues:

cond_A_pval cond_B_pval cond_C_pval
0.05    0.9 0.006

Here is my starting point:

pval<-apply(df,1,function(x) {t.test(x[1:3],x[4:6])$p.value})

Solution

Try the following:

df <- structure(list(ctrl_1 = 1L, ctrl_2 = 2L, ctrl_3 = 3L, cond_A_1 = 4L, 
               cond_A_2 = 4L, cond_A_3 = 4L, cond_B_1 = 5L, cond_B_2 = 5L, 
               cond_B_3 = 7L, cond_C_1 = 8L, cond_C_2 = 9L, cond_C_3 = 2L), 
               .Names = c("ctrl_1", "ctrl_2", "ctrl_3", 
                          "cond_A_1", "cond_A_2", "cond_A_3", 
                          "cond_B_1", "cond_B_2", "cond_B_3", 
                          "cond_C_1", "cond_C_2", "cond_C_3"), 
               class = "data.frame", row.names = c(NA, -1L))

library(tidyr)

# Reshape the data into key-value pairs. 
# It is generally advisable to have data in tidy format. 
df <- gather(df)
# Remove the _1, _2, etc. 
df$group <- gsub("_\\d", "", df$key)

#Now you can loop through the groups. Note that "ctrl" is the first group:
sapply(unique(df$group)[-1], function(x){
  t.test(df[df$group == "ctrl", "value"], df[df$group == x, "value"])$p.value 
})

 cond_A     cond_B     cond_C 
0.07417990 0.01477836 0.17957429