#' Training Phenotypic Age algorithm using the NHANES III and projecting into NHANES IV dataset.
#'
#' @title phenoage_nhanes
#' @description Train Phenotypic Age algorithm in NHANES III and project into NHANES IV.
#' @param biomarkers A character vector indicating the names of the biomarkers included in the Phenotypic Age algorithm.
#' @return An object of class "phenoage". This object is a list with two elements (data and fit). The dataset can be drawn by typing 'data'. The model can be drawn by typing 'fit'.
#' @examples
#' #Phenoage using NHANES
#' phenoage = phenoage_nhanes(biomarkers=c("albumin_gL","lymph","mcv","glucose_mmol",
#' "rdw","creat_umol","lncrp","alp","wbc"))
#'
#' #Extract phenoage dataset
#' data = phenoage$data
#'
#'
#' @export
#' @import dplyr
phenoage_nhanes = function(biomarkers) {
#develop training dataset for Levine's phenoage method
train = phenoage_calc(data = NHANES3 %>%
filter(age >= 20 & age <= 84) %>%
mutate(albumin = albumin_gL,
glucose = glucose_mmol,
creat = creat_umol,
lncreat = lncreat_umol),
biomarkers, fit=NULL)
#develop test dataset for Levine's phenoage method
test = phenoage_calc(data = NHANES4 %>%
filter(age >= 20) %>%
mutate(albumin = albumin_gL,
glucose = glucose_mmol,
creat = creat_umol,
lncreat = lncreat_umol),
biomarkers, fit=train$fit)
#comebine calculated phenoage
dat = left_join(NHANES4, test$data[,c("sampleID", "phenoage", "phenoage_advance")], by = "sampleID")
phenoage = list(data = dat, fit = train$fit)
class(phenoage) = append(class(phenoage), "phenoage")
return(phenoage)
}
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.