--- title: "CKB data" output: rmarkdown::html_vignette vignette: > %\VignetteIndexEntry{CKB data} %\VignetteEngine{knitr::rmarkdown} %\VignetteEncoding{UTF-8} --- ```{r, include = FALSE} knitr::opts_chunk$set( collapse = TRUE, comment = "#>" ) library(ckbtools) ``` Information about the CKB cohort data is available at [www.ckbiobank.org/data-access/data-overview](https://www.ckbiobank.org/data-access/data-overview). Details of the CKB Data Sharing Policy, data release schedules and data request application procedures are available at [www.ckbiobank.org/data-access](https://www.ckbiobank.org/data-access). This package includes the following entirely synthetic data sets, which have similar structure and variable names to real CKB data: * ckbtools_baseline * ckbtools_endpoints * ckbtools_endpoint_definitions * ckbtools_ckbtools_ascertainments * ckbtools_raw_olink_meta_data * ckbtools_raw_olink_protein_data * ckbtools_raw_somascan_meta_data * ckbtools_raw_somascan_protein_data * ckbtools_raw_somascan_sample_data A `ckbtools_participant_data` data set is also included in the package, which is derived from the synthetic raw data as below. ```{r, eval = FALSE} ckbtools_baseline$sex <- factor(ckbtools_baseline$is_female, levels = c(0, 1), labels = c("Male", "Female")) ckbtools_baseline$age_at_study_date <- ckbtools_baseline$age_at_study_date_x100 / 100 ckbtools_baseline$age_at_ckbtools_baseline_group <- cut(ckbtools_baseline$age_at_study_date, breaks = seq(30, 80, by = 10), right = FALSE) ckbtools_baseline$high_school_or_higher <- ckbtools_baseline$highest_education %in% c(3, 4, 5) ckbtools_baseline$education <- factor(ckbtools_baseline$highest_education, levels = c(0, 1, 2, 3, 4, 5), labels = c("No formal school", "Primary School", "Middle School", "High School", "Technical School / college", "University")) ckbtools_baseline$education_4_groups <- factor(ckbtools_baseline$highest_education, levels = c(0, 1, 2, 3, 4, 5), labels = c("No formal school", "Primary School", "Middle School", "High School or higher", "High School or higher", "High School or higher")) ckbtools_baseline$smoking <- factor(ckbtools_baseline$smoking_category, levels = c(1, 2, 3, 4), labels = c("Never smoker", "Occasional smoker", "Ex regular smoker", "Smoker")) ckbtools_baseline$smoking_3_groups <- factor(ckbtools_baseline$smoking_category, levels = c(1, 2, 3, 4), labels = c("Never / Occasional smoker", "Never / Occasional smoker", "Ex regular smoker", "Smoker")) ckbtools_baseline$current_regular_smoker <- factor(ckbtools_baseline$smoking_category, levels = c(1, 2, 3, 4), labels = c("No", "No", "No", "Yes")) ckbtools_baseline$alcohol_3_groups <- factor(ckbtools_baseline$alcohol_category, levels = c(1, 2, 3, 4, 5, 6), labels = c("Never regular drinker", "Weekly / Reduced / Ex", "Occasional / Monthly", "Occasional / Monthly", "Weekly / Reduced / Ex", "Weekly / Reduced / Ex")) ckbtools_baseline$bmi_grp <- cut(ckbtools_baseline$bmi_calc, c(0, 18.5, 25, 30, Inf), labels = c("<18.5", "18.5-25", "25-30", "30+"), right = FALSE) ckbtools_baseline$hours_since_last_ate <- ckbtools_baseline$hours_since_last_ate_x10 / 10 ckbtools_baseline$region <- factor(ckbtools_baseline$region_code, levels = c(12, 16, 26, 36, 46, 52, 58, 68, 78, 88), labels = c("Qingdao", "Harbin", "Haikou", "Suzhou", "Liuzhou", "Sichuan", "Gansu", "Henan", "Zhejiang", "Hunan")) ckbtools_endpoints$ihd <- ckbtools_endpoints$CKB0003_ep ckbtools_endpoints$ihd_date <- ckbtools_endpoints$CKB0003_datedeveloped ckbtools_endpoints$respiratory_diseases <- ckbtools_endpoints$CKB0032_ep ckbtools_endpoints$respiratory_diseases_date <- ckbtools_endpoints$CKB0032_datedeveloped ckbtools_endpoints <- ckbtools_endpoints[, c("csid", "ihd", "ihd_date", "respiratory_diseases", "respiratory_diseases_date")] ckbtools_baseline$all_cause_mortality_date <- ckbtools_baseline$censoring_date ckbtools_baseline$all_cause_mortality <- as.numeric(grepl("Dead", ckbtools_baseline$censoring_reason)) ckbtools_participant_data <- merge(ckbtools_baseline, ckbtools_endpoints, by = "csid") csid_in_subcohort <- ckbtools_ascertainments$csid[ckbtools_ascertainments$olinkexpexpan_chd_b1_subcohort == 1] ckbtools_participant_data$proteomics_subcohort <- as.numeric(ckbtools_participant_data$csid %in% csid_in_subcohort) ```