Some types of data or results are indexed by two identifiers in
two different columns corresponding to data points for pairs of
observations. E.g., you may have columns called id1 and id2 that index
the tibble for all possible pairs of results between samples A, B, and C.
If you attempt to join two tibbles with by=c("id1", "id2"), the join will
fail if samples are flipped from one dataset to another. E.g., one tibble
may have id1=A and id2=B while the other has id1=B and id2=A. This function
ensures that id1 is alphanumerically first while id2 is alphanumerically
second. See examples.
arrange_ids(.data, .id1, .id2)A tibble with two ID columns to arrange.
Unquoted name of the "id1" column. See examples.
Unquoted name of the "id2" column. See examples.
A tibble with id1 and id2 rearranged alphanumerically.
d1 <- tibble::tribble(
~id1, ~id2, ~results1,
"a", "b", 10L,
"a", "c", 20L,
"c", "b", 30L
)
d2 <- tibble::tribble(
~id1, ~id2, ~results2,
"b", "a", 101L,
"c", "a", 201L,
"b", "c", 301L
)
# Inner join fails because id1!=id2.
dplyr::inner_join(d1, d2, by=c("id1", "id2"))
#> # A tibble: 0 × 4
#> # … with 4 variables: id1 <chr>, id2 <chr>, results1 <int>, results2 <int>
# Arrange IDs
d1 %>% arrange_ids(id1, id2)
#> # A tibble: 3 × 3
#> id1 id2 results1
#> <chr> <chr> <int>
#> 1 a b 10
#> 2 a c 20
#> 3 b c 30
d2 %>% arrange_ids(id1, id2)
#> # A tibble: 3 × 3
#> id1 id2 results2
#> <chr> <chr> <int>
#> 1 a b 101
#> 2 a c 201
#> 3 b c 301
# Inner join
dplyr::inner_join(arrange_ids(d1, id1, id2), arrange_ids(d2, id1, id2), by=c("id1", "id2"))
#> # A tibble: 3 × 4
#> id1 id2 results1 results2
#> <chr> <chr> <int> <int>
#> 1 a b 10 101
#> 2 a c 20 201
#> 3 b c 30 301
# Recursively, if you had more than two tibbles
list(d1, d2) %>%
purrr::map(arrange_ids, id1, id2) %>%
purrr::reduce(dplyr::inner_join, by=c("id1", "id2"))
#> # A tibble: 3 × 4
#> id1 id2 results1 results2
#> <chr> <chr> <int> <int>
#> 1 a b 10 101
#> 2 a c 20 201
#> 3 b c 30 301