From c71877111f7d30f24fbb1bc82599a56e2b889676 Mon Sep 17 00:00:00 2001 From: Fabian Hee <45382374+f-meister@users.noreply.github.com> Date: Tue, 1 Oct 2024 17:45:00 +0800 Subject: [PATCH] Fix: rename spec doc, remove redundancies Also remove namespace resolution --- adam/adrs.qmd | 70 +++++++++--------- adam/adtte.qmd | 6 +- metadata/adam_spec.xlsx | Bin 8287946 -> 0 bytes .../adam_spec.xlsx => metadata/onco_spec.xlsx | Bin 4 files changed, 39 insertions(+), 37 deletions(-) delete mode 100644 metadata/adam_spec.xlsx rename adam/adam_spec.xlsx => metadata/onco_spec.xlsx (100%) diff --git a/adam/adrs.qmd b/adam/adrs.qmd index 2fbbcdb..26bbefd 100644 --- a/adam/adrs.qmd +++ b/adam/adrs.qmd @@ -26,7 +26,6 @@ library(xportr) library(pharmaversesdtm) library(pharmaverseadam) library(dplyr) -library(tidyr) library(lubridate) library(stringr) ``` @@ -36,8 +35,9 @@ library(stringr) Load the specifications stored in an Excel file into a `{metacore}` object. ```{r read-specs} -metacore <- metacore::spec_to_metacore("./metadata/adam_spec.xlsx") %>% - metacore::select_dataset("ADRS") +#| warning: false +metacore <- spec_to_metacore("../metadata/onco_spec.xlsx") %>% + select_dataset("ADRS") ``` # Load Source Datasets @@ -53,8 +53,8 @@ rs <- rs_onco_recist tu <- tu_onco_recist # Convert blanks to NA -rs <- admiral::convert_blanks_to_na(rs) -tu <- admiral::convert_blanks_to_na(tu) +rs <- convert_blanks_to_na(rs) +tu <- convert_blanks_to_na(tu) ``` # Merging ADSL with RS @@ -63,7 +63,7 @@ Merge `ADSL` to the `RS` domain by selecting only the necessary variables for de ```{r merge-adsl-rs} adsl_vars <- exprs(RANDDT) -adrs_merged <- admiral::derive_vars_merged( +adrs_merged <- derive_vars_merged( rs, dataset_add = adsl, new_vars = adsl_vars, @@ -80,8 +80,8 @@ Filter the `RS` domain to include only overall response records assessed by the ```{r set-param-details} adrs_ovr <- adrs_merged %>% - dplyr::filter(RSEVAL == "INVESTIGATOR" & RSTESTCD == "OVRLRESP") %>% - dplyr::mutate( + filter(RSEVAL == "INVESTIGATOR" & RSTESTCD == "OVRLRESP") %>% + mutate( PARAMCD = "OVR", PARAM = "Overall Response by Investigator", PARCAT1 = "Tumor Response", @@ -97,13 +97,13 @@ Impute missing dates and derive analysis dates and visits. ```{r impute-dates} adrs_imputed <- adrs_ovr %>% - admiral::derive_vars_dt( + derive_vars_dt( dtc = RSDTC, new_vars_prefix = "A", highest_imputation = "D", date_imputation = "last" ) %>% - dplyr::mutate(AVISIT = VISIT) + mutate(AVISIT = VISIT) head(adrs_imputed, n=10) ``` @@ -113,9 +113,9 @@ Populate `AVALC` with assessed values and create the numeric version `AVAL`. ```{r derive-aval} adrs_aval <- adrs_imputed %>% - dplyr::mutate( + mutate( AVALC = RSSTRESC, - AVAL = admiralonco::aval_resp(AVALC) + AVAL = aval_resp(AVALC) ) head(adrs_aval, n=10) ``` @@ -126,7 +126,7 @@ Flag the worst assessment at each date, considering only valid assessments from ```{r flag-worst-assessment} worst_resp <- function(arg) { - dplyr::case_when( + case_when( arg == "NE" ~ 1, arg == "CR" ~ 2, arg == "PR" ~ 3, @@ -138,9 +138,9 @@ worst_resp <- function(arg) { } adrs_anl01fl <- adrs_aval %>% - admiral::restrict_derivation( - derivation = admiral::derive_var_extreme_flag, - args = admiral::params( + restrict_derivation( + derivation = derive_var_extreme_flag, + args = params( by_vars = exprs(STUDYID, USUBJID, ADT), order = exprs(worst_resp(AVALC), RSSEQ), new_var = ANL01FL, @@ -155,11 +155,11 @@ head(adrs_anl01fl, n=10) ## Derive Progressive Disease Parameter -Use the `admiral::derive_extreme_records()` function to find the date of first `PD`. +Use the `derive_extreme_records()` function to find the date of first `PD`. ```{r derive-pd} adrs_pd <- adrs_anl01fl %>% - admiral::derive_extreme_records( + derive_extreme_records( dataset_ref = adsl, dataset_add = adrs_anl01fl, by_vars = exprs(STUDYID, USUBJID), @@ -174,7 +174,7 @@ adrs_pd <- adrs_anl01fl %>% PARCAT1 = "Tumor Response", PARCAT2 = "Investigator", PARCAT3 = "RECIST 1.1", - AVAL = admiral::yn_to_numeric(AVALC), + AVAL = yn_to_numeric(AVALC), ANL01FL = "Y" ) ) @@ -187,10 +187,10 @@ Create a new death parameter using the death date from `ADSL`. ```{r derive-death} adsldth <- adsl %>% - dplyr::select(STUDYID, USUBJID, DTHDT, !!!adsl_vars) + select(STUDYID, USUBJID, DTHDT, !!!adsl_vars) adrs_death <- adrs_pd %>% - admiral::derive_extreme_records( + derive_extreme_records( dataset_ref = adsldth, dataset_add = adsldth, by_vars = exprs(STUDYID, USUBJID), @@ -201,12 +201,12 @@ adrs_death <- adrs_pd %>% PARAMCD = "DEATH", PARAM = "Death", PARCAT1 = "Reference Event", - AVAL = admiral::yn_to_numeric(AVALC), + AVAL = yn_to_numeric(AVALC), ANL01FL = "Y", ADT = DTHDT ) ) %>% - dplyr::select(-DTHDT) + select(-DTHDT) head(adrs_death, n=10) ``` @@ -216,7 +216,7 @@ Create a parameter for the last disease assessment. ```{r derive-lsta} adrs_lsta <- adrs_death %>% - admiral::derive_extreme_records( + derive_extreme_records( dataset_ref = adsl, dataset_add = adrs_death, by_vars = exprs(STUDYID, USUBJID), @@ -241,11 +241,11 @@ Apply metadata and conduct checks to ensure data quality and compliance. ```{r apply-metadata-check, eval=FALSE} adrs_checked <- adrs_lsta %>% - metatools::drop_unspec_vars(metacore) %>% # Drop variables not specified in metadata - metatools::check_variables(metacore) %>% # Check all variables specified are present and no more - metatools::check_ct_data(metacore) %>% # Check controlled terminology - metatools::order_cols(metacore) %>% # Order columns according to metadata - metatools::sort_by_key(metacore) # Sort rows by sort keys + drop_unspec_vars(metacore) %>% # Drop variables not specified in metadata + check_variables(metacore) %>% # Check all variables specified are present and no more + check_ct_data(metacore) %>% # Check controlled terminology + order_cols(metacore) %>% # Order columns according to metadata + sort_by_key(metacore) # Sort rows by sort keys ``` # Apply Labels and Formats with xportr @@ -256,10 +256,10 @@ Finally, apply labels, formats, and export the dataset to an XPT file. dir <- tempdir() # Specify the directory for saving the XPT file adrs_xpt <- adrs_lsta %>% - xportr::xportr_type(metacore, domain = "ADRS") %>% # Coerce variable types to match metadata - xportr::xportr_length(metacore) %>% # Assign variable lengths from metadata - xportr::xportr_label(metacore) %>% # Assign variable labels from metadata - xportr::xportr_format(metacore) %>% # Assign variable formats from metadata - xportr::xportr_df_label(metacore) %>% # Assign dataset labels from metadata - xportr::xportr_write(file.path(dir, "adrs.xpt")) # Write the XPT file + xportr_type(metacore, domain = "ADRS") %>% # Coerce variable types to match metadata + xportr_length(metacore) %>% # Assign variable lengths from metadata + xportr_label(metacore) %>% # Assign variable labels from metadata + xportr_format(metacore) %>% # Assign variable formats from metadata + xportr_df_label(metacore) %>% # Assign dataset labels from metadata + xportr_write(file.path(dir, "adrs.xpt")) # Write the XPT file ``` diff --git a/adam/adtte.qmd b/adam/adtte.qmd index f202da0..4c3a96c 100644 --- a/adam/adtte.qmd +++ b/adam/adtte.qmd @@ -35,9 +35,11 @@ library(pharmaverseadam) We will load our specification file into a `{metacore}` object to trace the dataset variables and attributes. Then, we will read the source data (`adsl` and `adrs_onco`). -```{r, warni} +```{r read-specs} +#| warning: false + # Load metacore specifications -metacore <- spec_to_metacore("./metadata/adam_spec.xlsx") %>% +metacore <- spec_to_metacore("../metadata/onco_spec.xlsx") %>% select_dataset("ADTTE") # Load source datasets diff --git a/metadata/adam_spec.xlsx b/metadata/adam_spec.xlsx deleted file mode 100644 index 9da9d2fb426e8aa06cc2e83efeb88cf3ccca22b7..0000000000000000000000000000000000000000 GIT binary patch literal 0 HcmV?d00001 literal 8287946 zcmeFa30M=$wl<6-%IJhNIAEi#1{4sHNhJ!Rh$0SKXd;>kg#ZHLfQ(@dgc+s5h~j`? zPy_)*#;Ax)A|NUXG6?|#GS7jeKlVQ7x#ygF&)(ak|9w9HZ@1<1c2`w*Os!h$EmKu% z)xmwUW-k$$H*cPZghL@L@=t%nr|*f*C+*Lws{D$n(a#PPsYwL(xigij~Z@=&x9No2ekwjQVQTQ1zx{z|GX}`mUCbhNuP6Qvd2%cH6mg<@O zqC$AaRaLX{meLhiYTa3$=zcEJSnSJ?$-bHyoz$;ZBHMQ`oR1%M zQ5RYTb@*F+4PA7`+U(W``s{pvlhbxv9QGR5bTpmXecDGcs8i3wHFDF0IWD2L+cacyV!yb8|YJohZX|EAtomt686OH(Bjz 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