From 3d8e033c4e55b0a4f8227df8fe54b0bd975d9e74 Mon Sep 17 00:00:00 2001 From: rmgpanw Date: Tue, 14 Jun 2022 14:07:54 +0100 Subject: [PATCH] increment dev version (minor) - add extract_phenotypes2: this will replace extract_phenotypes()/related functions --- DESCRIPTION | 2 +- R/clinical_events.R | 191 ++++++++++++++++++++++++++ tests/testthat/test_clinical_events.R | 3 + 3 files changed, 195 insertions(+), 1 deletion(-) diff --git a/DESCRIPTION b/DESCRIPTION index 6bc7c1f..ca22412 100644 --- a/DESCRIPTION +++ b/DESCRIPTION @@ -1,7 +1,7 @@ Package: ukbwranglr Type: Package Title: Exploring UKB Data -Version: 0.0.0.9000 +Version: 0.0.0.9001 Authors@R: person("Alasdair", "Warwick", email = "alasdair.warwick06@gmail.com", role = c("aut", "cre")) Description: Functions to load and wrangle UK Biobank data. diff --git a/R/clinical_events.R b/R/clinical_events.R index 4194863..c5599ee 100644 --- a/R/clinical_events.R +++ b/R/clinical_events.R @@ -125,6 +125,197 @@ mutate_age_at_event_cols <- function(ukb_main, # Extract phenotypes from clinical events ------------------------------------------------------- +#' Extract phenotypes from clinical events data +#' +#' Filters a clinical events table created by \code{\link{tidy_clinical_events}} +#' for a set or sets of specified clinical codes that represent one or more +#' phenotypes. By default, the \emph{earliest} date that any clinical code +#' appears in an individual participant's record is extracted. See also the +#' \href{https://rmgpanw.github.io/ukbwranglr/articles/ukb_clinical_events.html}{'Clinical +#' events'} vignette on the \code{ukbwranglr} package website. +#' +#' @param clinical_events A long format data frame created by +#' \code{\link{tidy_clinical_events}}, \code{\link{tidy_gp_clinical}}, +#' \code{\link{tidy_gp_scripts}} or \code{\link{make_clinical_events_db}}. +#' This can also be a \code{\link[dbplyr]{tbl_dbi}} object. +#' @param clinical_codes data frame. Must match the format as per +#' \code{\link{example_clinical_codes}}. +#' @param data_sources A character vector of clinical events sources in +#' \code{clinical_events} to extract phenotypes from. Use +#' \code{\link{clinical_events_sources}} (\code{source column}) for a list of +#' valid values. +#' +#' @return A named list of data frames, one for each disease. Each data frame +#' has an "eid" column, and "event_min/max_indicator" and "event_min/max_date" +#' columns for each phenotype in the 'category' column of +#' \code{clinical_codes} for that disease. If \code{keep_all} is \code{TRUE}, +#' then there will also be additional nested data frame column called 'data'. +#' @export +#' @family clinical events +#' @examples +#' library(magrittr) +#' +#' # dummy clinical events data frame +#' dummy_ukb_data_dict <- get_ukb_dummy("dummy_Data_Dictionary_Showcase.tsv") +#' dummy_ukb_codings <- get_ukb_dummy("dummy_Codings.tsv") +#' +#' dummy_clinical_events <- read_ukb( +#' path = get_ukb_dummy("dummy_ukb_main.tsv", path_only = TRUE), +#' ukb_data_dict = dummy_ukb_data_dict, +#' ukb_codings = dummy_ukb_codings +#' ) %>% +#' tidy_clinical_events( +#' ukb_data_dict = dummy_ukb_data_dict, +#' ukb_codings = dummy_ukb_codings +#' ) %>% +#' dplyr::bind_rows() +#' +#' head(dummy_clinical_events) +#' +#' # dummy clinical code list +#' example_clinical_codes() +#' +#' # Filter for participants with matching clinical codes, +#' # by default only the earliest date is extracted +#' cases <- extract_phenotypes( +#' clinical_events = dummy_clinical_events, +#' clinical_codes = example_clinical_codes() +#' ) +#' +#' # returns a named list of data frames, one for each category in +#' # lower case, and one for the overall disease in capitals +#' cases +extract_phenotypes2 <- function(clinical_events, + clinical_codes, + eid_filter = NULL, + source_filter = NULL, + date_filter = NULL) { + + start_time <- proc.time() + + # validate args ----- + # clinical_events + validate_clinical_events_and_check_type(clinical_events) + + # clinical_codes + validate_clinical_codes(clinical_codes) + + # eid_filter + if (!is.null(eid_filter)) { + assertthat::assert_that(is.integer(eid_filter), + msg = "`eid_filter` should be type integer") + + assertthat::assert_that(assertthat::noNA(eid_filter), + msg = "`eid_filter` must not contain `NA` values") + } + + # source_filter + if (!is.null(source_filter)) { + assertthat::assert_that(is.character(source_filter), + msg = "`source_filter` should be type character") + + assertthat::assert_that(assertthat::noNA(source_filter), + msg = "`source_filter` must not contain `NA` values") + + invalid_data_sources <- + subset( + source_filter, + !source_filter %in% clinical_events_sources()$source + ) + + assertthat::assert_that( + length(invalid_data_sources) == 0, + msg = paste0( + "Error! The following values in `source_filter` are not valid: ", + stringr::str_c(invalid_data_sources, + sep = "", + collapse = ", ") + ) + ) + } + + ## check that date_filter contains valid dates + if (!is.null(date_filter)) { + assertthat::assert_that(is.character(date_filter), + msg = "`date_filter` should be type character") + + assertthat::assert_that(length(date_filter) == 2, + msg = "`date_filter` should be a character vector of length 2") + + invalid_dates <- date_filter %>% + purrr::map_chr(~ tryCatch({ + as.Date(.x) + NA_character_ + }, + error = function(e) + .x)) %>% + subset(!is.na(.)) + + assertthat::assert_that(length(invalid_dates) == 0, + msg = paste0( + "`date_filter` contains invalid values: ", + paste(invalid_dates, + collapse = ", ") + )) + + assertthat::assert_that(date_filter[1] < date_filter[2], + msg = "The second date of `date_filter` must be later than the first date") + } + + ## check that min date is greater than max date in date_filter + + + # filter `clinical_events` ------- + # filter `clinical_events` for codes in `clinical_codes` (regardless of code + # type at this stage) + clinical_events <- clinical_events %>% + dplyr::filter(.data[["code"]] %in% local(unique(clinical_codes$code))) + + # optional filters + if (!is.null(eid_filter)) { + clinical_events <- clinical_events %>% + dplyr::filter(.data[["eid"]] %in% local(unique(eid_filter))) + } + + if (!is.null(source_filter)) { + clinical_events <- clinical_events %>% + dplyr::filter(.data[["source"]] %in% local(unique(source_filter))) + } + + if (!is.null(date_filter)) { + clinical_events <- clinical_events %>% + dplyr::filter( + (.data[["date"]] < local(date_filter[1])) & + (.data[["date"]] >= local(date_filter[2])) + ) + } + + # collect from SQLITe db + clinical_events <- dplyr::collect(clinical_events) + + # join with `clinical_codes` --------- + # append code_type + source_to_code_type_map <- clinical_events_sources() %>% + dplyr::select(.data[["source"]], + "code_type" = .data[["data_coding"]]) + + # check that source-to-code_type mapping table has only unique values under `source` col + stopifnot( + dplyr::n_distinct(source_to_code_type_map$source) == nrow(source_to_code_type_map) + ) + + clinical_events <- clinical_events %>% + dplyr::left_join(source_to_code_type_map, + by = "source") + + # perform filtering join with clinical codelist + clinical_events %>% + dplyr::inner_join(clinical_codes %>% + dplyr::select(-.data[["description"]]), + by = c("code", + "code_type")) +} + #' Extract phenotypes from clinical events data #' #' Filters a clinical events table created by \code{\link{tidy_clinical_events}} diff --git a/tests/testthat/test_clinical_events.R b/tests/testthat/test_clinical_events.R index 227324c..3584924 100644 --- a/tests/testthat/test_clinical_events.R +++ b/tests/testthat/test_clinical_events.R @@ -77,6 +77,9 @@ stopifnot(validate_clinical_codes(dummy_clinical_codes)) # TESTS ------------------------------------------------------------------- +result2 <- extract_phenotypes2(clinical_events = dummy_clinical_events_db, + clinical_codes = dummy_clinical_codes) + # `tidy_clinical_events_basis()` ----------------------------------------- test_that("`tidy_clinical_events_basis()` removes empty string values", {