Build group using Orphanet classifications

This is a method for the dplyr group_by() generic. It extends initial groups by adding rows containing descendants ORPHAcodes. This way any row may belong to several groups.

The function will force the creation of groups (they may be empty) for any ORPHAcode provided in force_codes argument when orpha_df() is called.

Usage

# S3 method for class 'orpha_df'
group_by(.data, ...)

Arguments

.data

An orpha_df() instantiation.

...

In group_by(), variables or computations to group by. Computations are always done on the ungrouped data frame. To perform computations on the grouped data, you need to use a separate mutate() step before the group_by(). Computations are not allowed in nest_by(). In ungroup(), variables to remove from the grouping.

Examples

library(dplyr)

# Build patients data.frame
df_patients = data.frame(
  patient_id = c(1,2,3,4,5,6),
  group = c('A','A','A','B','B','B'),
  code = c('158673', '595356', '305', '79406', '79406', '595356'))

df_counts = df_patients %>% group_by(code)
attr(df_counts, 'groups')
#> # A tibble: 4 × 2
#>   code         .rows
#>   <chr>  <list<int>>
#> 1 158673         [1]
#> 2 305            [1]
#> 3 595356         [2]
#> 4 79406          [2]

df_counts = df_patients %>% orpha_df(orpha_code_col = 'code') %>% group_by(code)
attr(df_counts, 'groups')
#> # A tibble: 4 × 2
#>   code   .rows    
#>   <chr>  <list>   
#> 1 158673 <int [1]>
#> 2 305    <int [3]>
#> 3 595356 <int [3]>
#> 4 79406  <int [2]>

df_counts = df_patients %>% orpha_df(orpha_code_col = 'code') %>% group_by(code, group)
attr(df_counts, 'groups')
#> # A tibble: 6 × 3
#> # Groups:   code [4]
#>   code   group .rows    
#>   <chr>  <chr> <list>   
#> 1 158673 A     <int [1]>
#> 2 305    A     <int [1]>
#> 3 305    B     <int [2]>
#> 4 595356 A     <int [2]>
#> 5 595356 B     <int [1]>
#> 6 79406  B     <int [2]>