Last updated: 2022-06-14
Checks: 5 2
Knit directory: codemapper_notes/
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library(tidyverse)
library(reactable)
library(readxl)
library(crosstalk)
library(targets)
library(codemapper)
library(flextable)
tar_load(ALL_LKPS_MAPS_DB)
con <- DBI::dbConnect(RSQLite::SQLite(), ALL_LKPS_MAPS_DB)
all_lkps_maps <- ukbwranglr::db_tables_to_list(con)
# read-opcs4 mapping tables
read_v2_opcs4 <- all_lkps_maps$read_v2_opcs4 %>%
collect()
read_ctv3_opcs4 <- all_lkps_maps$read_ctv3_opcs4 %>%
collect()
read_codes_that_map_to_opcs4 <- list(
read2 = read_v2_opcs4,
read3 = read_ctv3_opcs4
) %>%
map(~ unique(.x$read_code))
# caliber codes - filter for diseases including opcs4 codes, then filter for OPCS4/read codes only, then filter read codes for only those that can map to OPCS4
tar_load(caliber_codes)
caliber_codes_operations <- caliber_codes %>%
# diseases that include OPCS4 codes
group_by(disease) %>%
mutate(disease_includes_opcs4 = case_when("opcs4" %in% code_type ~ TRUE,
TRUE ~ FALSE)) %>%
ungroup() %>%
filter(disease_includes_opcs4) %>%
select(-disease_includes_opcs4) %>%
# filter for opcs4 codes, and read codes that can map to OPCS4
filter(
(code_type == "opcs4") |
((code_type == "read2") & (code %in% read_codes_that_map_to_opcs4$read2)) |
((code_type == "read3") & (code %in% read_codes_that_map_to_opcs4$read3))
)
# self-reported UKB non-cancer illnesses
coding5 <- tar_read(ukb_codings) %>%
filter(Coding == "5")Aim: to assign UKB self-reported operation codes to CALIBER conditions.
Approach:
coding5 %>%
select(-Coding,
data_coding_5 = Value,
ukb_meaning = Meaning) %>%
reactable(filterable = TRUE,
searchable = TRUE,
paginationType = "jump",
showPageSizeOptions = TRUE,
resizable = TRUE,
pageSizeOptions = c(10, 25, 50, 100, 200, 300, 350))caliber_codes_operations %>%
distinct(disease) %>%
reactable(filterable = TRUE,
paginationType = "jump",
showPageSizeOptions = TRUE,
resizable = TRUE,
pageSizeOptions = c(10, 30))# write to csv
ukb_self_report_operations_to_caliber_map_unselected <-
caliber_codes_operations %>%
distinct(disease) %>%
mutate(
description = "",
category = "UKB self-reported",
code_type = "data_coding_5",
code = "",
author = "caliber"
)
ukb_self_report_operations_to_caliber_map_unselected %>%
write_csv(here::here(file.path("data_small",
"ukb_self_report_operations_to_caliber_map_raw.csv")))
# NOTE: when manually reviewing, save the csv as a separate file without the '_raw' suffix# test that `ukb_self_report_non_cancer_to_caliber_map.csv` contains the same mappings as `ukb_self_report_non_cancer_to_caliber_map_raw.csv` (apart from the manuall mapping column) - RAISE ERROR AND HALT KNITTING IF NOT
ukb_self_report_operations_to_caliber_map <- read_csv(here::here(file.path("data_small",
"ukb_self_report_operations_to_caliber_map.csv")),
col_types = readr::cols(.default = "c"))
assertthat::are_equal(
x = ukb_self_report_operations_to_caliber_map %>%
distinct(disease) %>%
arrange(),
y = ukb_self_report_operations_to_caliber_map_unselected %>%
distinct(disease) %>%
arrange(),
msg = "Manually selected mapping csv does not match 'ukb_self_report_operations_to_caliber_map_raw.csv'. These should contain the same values under column 'disease'. Has the raw version been updated?"
)
# general validation checks
ukb_self_report_operations_to_caliber_map %>%
filter(selected == "Y") %>%
select(-selected) %>%
ukbwranglr::validate_clinical_codes()| CALIBER disease | Potential issues |
|---|---|
| End stage renal disease | Includes OPCS4 code for ‘Pre-transplantation of kidney work-up - recipient’ (‘M172’). |
| Glaucoma | Includes procedures (such as laser treatments and operations on the iris) that are not covered by the UKB self-reported code ‘glaucoma surgery/trabeculectomy’. |
| Peripheral arterial disease | Includes procedures (such as endarterectomy, embolectomy, reconstruction) that are not covered by the UKB self-reported codes ‘fem-pop bypass/leg artery bypass’ and ‘leg artery angioplasty +/- stent’. |
list(caliber_codes_operations,
ukb_self_report_operations_to_caliber_map) %>%
bind_rows() %>%
filter(code_type %in% c("opcs4",
"data_coding_5")) %>%
filter(disease %in% c(
"End stage renal disease",
"Glaucoma",
"Peripheral arterial disease"
)) %>%
select(all_of(names(ukbwranglr::example_clinical_codes()))) %>%
reactable(
filterable = TRUE,
paginationType = "jump",
showPageSizeOptions = TRUE,
resizable = TRUE,
pageSizeOptions = c(10, 30)
)ukb_self_report_operations_to_caliber_map %>%
mutate(selected = case_when(is.na(selected) ~ "N",
TRUE ~ selected)) %>%
reactable(filterable = TRUE,
searchable = TRUE,
paginationType = "jump",
showPageSizeOptions = TRUE,
pageSizeOptions = c(10, 25, 50))ukb_self_report_operations_to_caliber_map %>%
filter(selected == "Y") %>%
select(-selected) %>%
bind_rows(caliber_codes_operations) %>%
arrange(disease,
category,
code_type) %>%
reactable(filterable = TRUE,
searchable = TRUE,
paginationType = "jump",
showPageSizeOptions = TRUE,
resizable = TRUE,
pageSizeOptions = c(10, 25, 50, 100, 200, 300, 350))
sessionInfo()R version 4.2.0 (2022-04-22)
Platform: x86_64-apple-darwin17.0 (64-bit)
Running under: macOS Big Sur/Monterey 10.16
Matrix products: default
BLAS: /Library/Frameworks/R.framework/Versions/4.2/Resources/lib/libRblas.0.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/4.2/Resources/lib/libRlapack.dylib
locale:
[1] en_GB.UTF-8/en_GB.UTF-8/en_GB.UTF-8/C/en_GB.UTF-8/en_GB.UTF-8
attached base packages:
[1] stats graphics grDevices datasets utils methods base
other attached packages:
[1] flextable_0.7.0 codemapper_0.0.0.9001 targets_0.12.0
[4] crosstalk_1.2.0 readxl_1.4.0 reactable_0.3.0
[7] forcats_0.5.1 stringr_1.4.0 dplyr_1.0.9
[10] purrr_0.3.4 readr_2.1.2 tidyr_1.2.0
[13] tibble_3.1.7 ggplot2_3.3.5 tidyverse_1.3.1
[16] workflowr_1.7.0
loaded via a namespace (and not attached):
[1] fs_1.5.2 bit64_4.0.5 lubridate_1.8.0
[4] httr_1.4.2 rprojroot_2.0.3 tools_4.2.0
[7] backports_1.4.1 bslib_0.3.1 utf8_1.2.2
[10] R6_2.5.1 DBI_1.1.2 colorspace_2.0-3
[13] withr_2.5.0 tidyselect_1.1.2 processx_3.5.3
[16] bit_4.0.4 compiler_4.2.0 git2r_0.30.1
[19] cli_3.3.0 rvest_1.0.2 xml2_1.3.3
[22] officer_0.4.2 sass_0.4.1 scales_1.2.0
[25] callr_3.7.0 systemfonts_1.0.4 digest_0.6.29
[28] rmarkdown_2.14 base64enc_0.1-3 pkgconfig_2.0.3
[31] htmltools_0.5.2 dbplyr_2.2.0 fastmap_1.1.0
[34] highr_0.9 htmlwidgets_1.5.4 rlang_1.0.2
[37] RSQLite_2.2.14 rstudioapi_0.13 shiny_1.7.1
[40] jquerylib_0.1.4 generics_0.1.2 jsonlite_1.8.0
[43] vroom_1.5.7 zip_2.2.0 magrittr_2.0.3
[46] Rcpp_1.0.8.3 munsell_0.5.0 fansi_1.0.3
[49] gdtools_0.2.4 lifecycle_1.0.1 stringi_1.7.6
[52] whisker_0.4 yaml_2.3.5 blob_1.2.3
[55] grid_4.2.0 parallel_4.2.0 promises_1.2.0.1
[58] crayon_1.5.1 haven_2.5.0 hms_1.1.1
[61] knitr_1.39 ps_1.7.0 pillar_1.7.0
[64] uuid_1.1-0 igraph_1.3.1 base64url_1.4
[67] codetools_0.2-18 reprex_2.0.1 glue_1.6.2
[70] evaluate_0.15 getPass_0.2-2 ukbwranglr_0.0.0.9000
[73] data.table_1.14.2 renv_0.13.2 modelr_0.1.8
[76] vctrs_0.4.1 tzdb_0.3.0 httpuv_1.6.5
[79] cellranger_1.1.0 gtable_0.3.0 reactR_0.4.4
[82] assertthat_0.2.1 cachem_1.0.6 xfun_0.30
[85] mime_0.12 xtable_1.8-4 broom_0.8.0
[88] later_1.3.0 memoise_2.0.1 ellipsis_0.3.2
[91] here_1.0.1