fisher.test on subset & summarized data frames using dplyr

dplyr_fisher_test.R

# here's what the data looks like:
> all_chrs_dt
        lower   upper signif_label signif_unlabel not_signif_label not_signif_unlabel                    test_name
   1:       0  100000         1293           1121          1235366             224096 unnannotated to unnannotated
   2:  100000  200000          465           1335          1244847             227812 unnannotated to unnannotated
   3:  200000  300000         1296           2358          1244090             225916 unnannotated to unnannotated
   4:  300000  400000         1245           1840          1242731             226852 unnannotated to unnannotated
   5:  400000  500000          627            995          1241226             227550 unnannotated to unnannotated
  ---                                                                                                             
5056: 1500000 1600000            0             76                0             895216               DNase to DNase
5057: 1600000 1700000            0            107                2             893980               DNase to DNase
5058: 1700000 1800000            0            162                1             891953               DNase to DNase
5059: 1800000 1900000            0             98                1             890585               DNase to DNase
5060: 1900000 2000000            0             78                1             889103               DNase to DNase
      chromosome
   1:       chr1
   2:       chr1
   3:       chr1
   4:       chr1
   5:       chr1
  ---           
5056:       chrX
5057:       chrX
5058:       chrX
5059:       chrX
5060:       chrX

# I'm trying to do fisher.test on bands of lower & upper e.g lower = 0 & upper = 100000
# For a given value of upper, I can get the row containing what I need in a df like so:

> counts <- all_chrs_dt %>% group_by(test_name) %>% filter(upper == 100000) %>% summarise(all_significant_label = sum(signif_label), all_significant_unlabel = sum(signif_unlabel), all_not_significant_label = sum(not_signif_label), all_not_significant_unlabel = sum(not_signif_unlabel))
> counts
Source: local data table [11 x 5]

                      test_name all_significant_label all_significant_unlabel all_not_significant_label
1  unnannotated to unnannotated                 15506                   10712                  15203321
2          unnannotated to CTCF                  2879                   23339                   1245936
3   unnannotated to DNase-K27ac                  5448                   20770                    804284
4         unnannotated to DNase                   267                   25951                    113358
5           CTCF to DNase-K27ac                   711                   25507                     57430
6                  CTCF to CTCF                   359                   25859                     41148
7    DNase-K27ac to DNase-K27ac                   967                   25251                     29548
8                 CTCF to DNase                    32                   26186                      7094
9          DNase to DNase-K27ac                    40                   26178                      4456
10         DNase-K27ac to DNase                     2                   26216                       811
11               DNase to DNase                     7                   26211                       618
Variables not shown: all_not_significant_unlabel (int)
 
 # I'd like to apply fisher.test to each row of this df, but I don't seem to be able to form the contingency tables 
 # properly
 
 > counts <- all_chrs_dt %>% group_by(test_name) %>% filter(upper == 100000) %>% summarise(all_significant_label = sum(signif_label), all_significant_unlabel = sum(signif_unlabel), all_not_significant_label = sum(not_signif_label), all_not_significant_unlabel = sum(not_signif_unlabel)) %>% group_by(test_name) %>% fisher.test(matrix(c(all_significant_label,all_significant_unlabel,all_not_significant_label, all_not_significant_unlabel),nrow=2,ncol=2))[[p.value]]
Error in `[[.data.frame`(., fisher.test(matrix(c(all_significant_label,  : 
  object 'p.value' not found
 
 >counts <- all_chrs_dt %>% group_by(test_name) %>% filter(upper == 100000) %>% summarise(all_significant_label = sum(signif_label), all_significant_unlabel = sum(signif_unlabel), all_not_significant_label = sum(not_signif_label), all_not_significant_unlabel = sum(not_signif_unlabel)) %>% group_by(test_name) %>% fisher.test(matrix(c(all_significant_label,all_significant_unlabel,all_not_significant_label, all_not_significant_unlabel),nrow=2,ncol=2))
Error in fisher.test(., matrix(c(all_significant_label, all_significant_unlabel,  : 
  all entries of 'x' must be nonnegative and finite