Join microorganisms to a Data Set — join • AMR (for R)

Join the data set microorganisms easily to an existing data set or to a character vector.

Usage

inner_join_microorganisms(x, by = NULL, suffix = c("2", ""), ...)

left_join_microorganisms(x, by = NULL, suffix = c("2", ""), ...)

right_join_microorganisms(x, by = NULL, suffix = c("2", ""), ...)

full_join_microorganisms(x, by = NULL, suffix = c("2", ""), ...)

semi_join_microorganisms(x, by = NULL, ...)

anti_join_microorganisms(x, by = NULL, ...)

Arguments

x: existing data set to join, or character vector. In case of a character vector, the resulting data.frame will contain a column 'x' with these values.
by: a variable to join by - if left empty will search for a column with class mo (created with as.mo()) or will be "mo" if that column name exists in x, could otherwise be a column name of x with values that exist in microorganisms$mo (such as by = "bacteria_id"), or another column in microorganisms (but then it should be named, like by = c("bacteria_id" = "fullname"))
suffix: if there are non-joined duplicate variables in x and y, these suffixes will be added to the output to disambiguate them. Should be a character vector of length 2.
...: ignored, only in place to allow future extensions

Value

a data.frame

Details

Note: As opposed to the join() functions of dplyr, character vectors are supported and at default existing columns will get a suffix "2" and the newly joined columns will not get a suffix.

If the dplyr package is installed, their join functions will be used. Otherwise, the much slower merge() and interaction() functions from base R will be used.

Examples

left_join_microorganisms(as.mo("K. pneumoniae"))
#> # A tibble: 1 × 26
#>   mo           fullname   status kingdom phylum class order family genus species
#>   <mo>         <chr>      <chr>  <chr>   <chr>  <chr> <chr> <chr>  <chr> <chr>  
#> 1 B_KLBSL_PNMN Klebsiell… accep… Bacter… Pseud… Gamm… Ente… Enter… Kleb… pneumo…
#> # ℹ 16 more variables: subspecies <chr>, rank <chr>, ref <chr>,
#> #   oxygen_tolerance <chr>, source <chr>, lpsn <chr>, lpsn_parent <chr>,
#> #   lpsn_renamed_to <chr>, mycobank <chr>, mycobank_parent <chr>,
#> #   mycobank_renamed_to <chr>, gbif <chr>, gbif_parent <chr>,
#> #   gbif_renamed_to <chr>, prevalence <dbl>, snomed <list>
left_join_microorganisms("B_KLBSL_PNMN")
#> # A tibble: 1 × 26
#>   mo           fullname   status kingdom phylum class order family genus species
#>   <mo>         <chr>      <chr>  <chr>   <chr>  <chr> <chr> <chr>  <chr> <chr>  
#> 1 B_KLBSL_PNMN Klebsiell… accep… Bacter… Pseud… Gamm… Ente… Enter… Kleb… pneumo…
#> # ℹ 16 more variables: subspecies <chr>, rank <chr>, ref <chr>,
#> #   oxygen_tolerance <chr>, source <chr>, lpsn <chr>, lpsn_parent <chr>,
#> #   lpsn_renamed_to <chr>, mycobank <chr>, mycobank_parent <chr>,
#> #   mycobank_renamed_to <chr>, gbif <chr>, gbif_parent <chr>,
#> #   gbif_renamed_to <chr>, prevalence <dbl>, snomed <list>

df <- data.frame(
  date = seq(
    from = as.Date("2018-01-01"),
    to = as.Date("2018-01-07"),
    by = 1
  ),
  bacteria = as.mo(c(
    "S. aureus", "MRSA", "MSSA", "STAAUR",
    "E. coli", "E. coli", "E. coli"
  )),
  stringsAsFactors = FALSE
)
colnames(df)
#> [1] "date"     "bacteria"

df_joined <- left_join_microorganisms(df, "bacteria")
colnames(df_joined)
#>  [1] "date"                "bacteria"            "fullname"           
#>  [4] "status"              "kingdom"             "phylum"             
#>  [7] "class"               "order"               "family"             
#> [10] "genus"               "species"             "subspecies"         
#> [13] "rank"                "ref"                 "oxygen_tolerance"   
#> [16] "source"              "lpsn"                "lpsn_parent"        
#> [19] "lpsn_renamed_to"     "mycobank"            "mycobank_parent"    
#> [22] "mycobank_renamed_to" "gbif"                "gbif_parent"        
#> [25] "gbif_renamed_to"     "prevalence"          "snomed"             

# \donttest{
if (require("dplyr")) {
  example_isolates %>%
    left_join_microorganisms() %>%
    colnames()
}
#> Joining, by = "mo"
#>  [1] "date"                "patient"             "age"                
#>  [4] "gender"              "ward"                "mo"                 
#>  [7] "PEN"                 "OXA"                 "FLC"                
#> [10] "AMX"                 "AMC"                 "AMP"                
#> [13] "TZP"                 "CZO"                 "FEP"                
#> [16] "CXM"                 "FOX"                 "CTX"                
#> [19] "CAZ"                 "CRO"                 "GEN"                
#> [22] "TOB"                 "AMK"                 "KAN"                
#> [25] "TMP"                 "SXT"                 "NIT"                
#> [28] "FOS"                 "LNZ"                 "CIP"                
#> [31] "MFX"                 "VAN"                 "TEC"                
#> [34] "TCY"                 "TGC"                 "DOX"                
#> [37] "ERY"                 "CLI"                 "AZM"                
#> [40] "IPM"                 "MEM"                 "MTR"                
#> [43] "CHL"                 "COL"                 "MUP"                
#> [46] "RIF"                 "fullname"            "status"             
#> [49] "kingdom"             "phylum"              "class"              
#> [52] "order"               "family"              "genus"              
#> [55] "species"             "subspecies"          "rank"               
#> [58] "ref"                 "oxygen_tolerance"    "source"             
#> [61] "lpsn"                "lpsn_parent"         "lpsn_renamed_to"    
#> [64] "mycobank"            "mycobank_parent"     "mycobank_renamed_to"
#> [67] "gbif"                "gbif_parent"         "gbif_renamed_to"    
#> [70] "prevalence"          "snomed"             
# }