#' Plot survival data of individuals
#'
#' This function provides the survival plot from individual metadata.
#'
#' @param data The object returned by the `pgxLoader` function, which includes survival data about individuals.
#' @param group_id A string specifying which column is used for grouping in the Kaplan-Meier plot.
#' @param condition A string for splitting individuals into younger and older groups, following the ISO 8601 duration format. Only used if `group_id` is "age_iso".
#' @param return_data A logical value determining whether to return the metadata used for plotting. Default is FALSE.
#' @param ... Other parameters relevant to KM plot. These include `pval`, `pval.coord`, `pval.method`, `conf.int`, `linetype`, and `palette` (see ggsurvplot from survminer)
#' @return The KM plot from input data
#' @export
#' @examples
#' individuals <- pgxLoader(type="individuals",filters="NCIT:C3512")
#' pgxMetaplot(individuals, group_id="age_iso", condition="P65Y")
pgxMetaplot <- function(data, group_id, condition, return_data = FALSE,...){
# remove samples without survival data
meta.sel.df <- data[!is.na(data$followup_time) & !data$followup_state_id %in% c('EFO:0030039','',NA),]
if(nrow(meta.sel.df) == 0) stop("\n No available survival data \n")
# transform ISOdate interal to days
plot_followup_time <- lubridate::time_length(meta.sel.df$followup_time,unit='day')
# process group id
## for age related group id
if (group_id == "age_iso"){
plot_group_time <- meta.sel.df[,group_id]
time_condition <- condition
### transform to days for comparison
plot_group_time <- lubridate::time_length(plot_group_time,unit='day')
time_condition <- lubridate::time_length(time_condition,unit='day')
if (is.numeric(condition) | is.na(time_condition)) stop("\n `condition` argument is invalid \n")
### split group
plot_group_id <- rep(NA,length(plot_group_time))
plot_group_id[plot_group_time > time_condition] <- paste0("Age>",condition)
plot_group_id[plot_group_time <= time_condition] <- paste0("Age<=",condition)
## for other group ids
} else{
plot_group_id <- meta.sel.df[,group_id]
}
# Map EFO code to numerical representation for plotting
plot_followup_state_id <- meta.sel.df$followup_state_id
plot_followup_state_id[plot_followup_state_id == "EFO:0030041"] <- 0 # alive
plot_followup_state_id[plot_followup_state_id == "EFO:0030049"] <- 1 # death
plot_followup_state_id <- as.numeric(plot_followup_state_id)
# fit
plot_data <- data.frame(followup_time=plot_followup_time, followup_state=plot_followup_state_id, group=plot_group_id)
sfit <- survival::survfit(survival::Surv(followup_time,followup_state)~group,data=plot_data)
splot.op <- list(
fit=sfit,
data=plot_data,
palette=NULL,
linetype=1,
conf.int=FALSE,
pval = FALSE,
pval.method=FALSE,
pval.coord = NULL,
ggtheme=ggplot2::theme_light()
)
splot.op <- modifyList(splot.op,list(...))
ggp <- do.call(survminer::ggsurvplot,splot.op)
show(ggp$plot)
if (return_data) return(meta.sel.df)
}
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