R/data_reform.R

In UKB.COVID19: UK Biobank COVID-19 Data Processing and Risk Factor Association Tests

#' Reform variables
#'
#' @param res Merged data of phenotype from makePhenotypes or comorbidity_summary and covariates from risk_factor.
#' @param type Data type: susceptibility, severity, mortality or comorbidity.
#' @keywords reform
#' @return Reformed data for association tests using logistic regression models.
#' @export data_reform

# reform data
data_reform <- function(res, type){
  res$ID <- as.character(res$ID)
  if(type == "cov"){
    res$sex <- as.factor(res$sex)
    res$ethnic <- as.factor(res$ethnic)
    res$other.ppl <- as.factor(res$other.ppl)
    res$black <- as.factor(res$black)
    res$asian <- as.factor(res$asian)
    res$mixed <- as.factor(res$mixed)
    res$white <- as.factor(res$white)
    #  res$array <- as.factor(res$array)
    
    if(any("blood_group" %in% colnames(res))){
      res$blood_group <- as.factor(res$blood_group)
      res$O <- as.factor(res$O)
      res$AB <- as.factor(res$AB)
      res$A <- as.factor(res$A)
      res$B <- as.factor(res$B)
    } 
    res$inAgedCare <- as.factor(res$inAgedCare)
    res[is.na(res$ethnic),c("other.ppl","black","asian","mixed","white")] <- NA
    res[is.na(res$inAgedCare),"inAgedCare"] <- 0
  }
  
  if(type == "susceptibility"){
    res$ppl.result <- as.factor(res$ppl.result)
    res$result <- as.factor(res$result)
  }
  
  if(type == "mortality") {
    res$mortality <- as.factor(res$mortality)
  }
  
  if(type == "severity") {
    res$mortality <- as.factor(res$mortality)
    res$hospitalisation <- as.factor(res$hospitalisation)
    res$critical.care <- as.factor(res$critical.care)
    res$advanced.critical.care <- as.factor(res$advanced.critical.care)
  }
  
  if(type == "comorbidity") {
    comorb.name <- colnames(res)[-1]
    for(j in 1:length(comorb.name)) res[,comorb.name[j]] <- as.factor(res[,comorb.name[j]])
  }
  
  attr(res, "class") <- "data.frame"
  res
}