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filter omop concepts by standard attributes

Source: R/omop_filter_concepts.R
omop_filter_concepts.Rd

Works on a dataframe or an arrow object. Can filter by one or more of : concept_id, domain_id, vocabulary_id, concept_class_id, standard_concept used by other functions

Usage

omop_filter_concepts(
  df,
  c_ids = NULL,
  d_ids = NULL,
  v_ids = NULL,
  cc_ids = NULL,
  standard = NULL
)

Arguments

df

dataframe with standard omop concept table columns

c_ids

one or more concept_id to filter by, default NULL for all

d_ids

one or more domain_id to filter by, default NULL for all

v_ids

one or more vocabulary_id to filter by, default NULL for all

cc_ids

one or more concept_class_id to filter by, default NULL for all

standard

one or more standard_concept to filter by, default NULL for all, S,C

Value

a filtered dataframe of concepts and attributes

Examples

omop_concept() |>
  omop_filter_concepts(d_ids=c("measurement","drug"),v_ids="SNOMED") |>
  dplyr::collect() |>
  dplyr::count(domain_id,vocabulary_id)
#> # A tibble: 2 × 3
#>   domain_id   vocabulary_id      n
#>   <chr>       <chr>          <int>
#> 1 Drug        SNOMED        254167
#> 2 Measurement SNOMED         39066
omop_concept() |> omop_filter_concepts(v_ids="Gender") |> dplyr::collect()
#> # A tibble: 5 × 10
#>   concept_id concept_name domain_id vocabulary_id concept_class_id
#>        <int> <chr>        <chr>     <chr>         <chr>           
#> 1       8570 AMBIGUOUS    Gender    Gender        Gender          
#> 2       8532 FEMALE       Gender    Gender        Gender          
#> 3       8507 MALE         Gender    Gender        Gender          
#> 4       8521 OTHER        Gender    Gender        Gender          
#> 5       8551 UNKNOWN      Gender    Gender        Gender          
#> # ℹ 5 more variables: standard_concept <chr>, concept_code <chr>,
#> #   valid_start_date <date>, valid_end_date <date>, invalid_reason <chr>