R/MMRFmethylation.R

In MarzyUnicz/MMRFBiolinks:

#' @title Creates survival analysis
#' @description Creates a survival plot from MMRF patient clinical data
#' using survival library. It uses the fields days_to_death and vital, plus a
#' columns for groups.
#'
#' @param clin.mm MMRF Clinical patient with the information days_to_death
#' @param clusterCol Column with groups to plot. This is a mandatory field, the
#' caption will be based in this column
#' @param legend Legend title of the figure
#' @param xlim x axis limits e.g. xlim = c(0, 1000). Present narrower X axis, but not affect survival estimates.
#' @param main main title of the plot
#' @param labels labels of the plot
#' @param ylab y axis text of the plot
#' @param xlab x axis text of the plot
#' @param filename The name of the pdf file.
#' @param color Define the colors/Pallete for lines.
#' @param risk.table show or not the risk table
#' @param width Image width
#' @param height Image height
#' @param pvalue show p-value of log-rank test
#' @param conf.int  show confidence intervals for point estimates of survival curves.
#' @param dpi Figure quality
#' @importFrom survminer ggsurvplot
#' @importFrom survival survfit Surv
#' @importFrom scales percent
#' @importFrom ggthemes theme_base
#' @importFrom ggrepel geom_text_repel
#' @importFrom gridExtra gtable_rbind
#' @importFrom TCGAbiolinks TCGAanalyze_survival
#' @export
#' @return Survival plot
#' @examples
#'  # clin.mm<-MMRFqueryGDC_clinic(type = "clinical")
#'  clin.mm <- data.frame(
#'       vital_status = c("alive","alive","alive","dead","alive",
#'                        "alive","dead","alive","dead","alive"),
#'       days_to_death = c(NA,NA,NA,172,NA,NA,3472,NA,786,NA),
#'       days_to_last_follow_up = c(3011,965,718,NA,1914,423,NA,5,656,1417),
#'       gender = c(rep("male",5),rep("female",5))
#'  )
#' MMRFanalyzeGDC_survival(clin.mm, clusterCol="gender")
#' MMRFanalyzeGDC_survival(clin.mm, clusterCol="gender", xlim = 1000)
#' MMRFanalyzeGDC_survival(clin.mm,
#'                        clusterCol="gender",
#'                        risk.table = FALSE,
#'                        conf.int = FALSE,
#'                        color = c("pink","blue"))
#' MMRFanalyzeGDC_survival(clin.mm,
#'                         clusterCol="gender",
#'                         risk.table = FALSE,
#'                         xlim = c(100,1000),
#'                         conf.int = FALSE,
#'                         color = c("Dark2"))
MMRFanalyzeGDC_survival <- function(clin.mm,
                                    clusterCol = NULL,
                                    legend = "Legend",
                                    labels = NULL,
                                    risk.table = TRUE,
                                    xlim = NULL,
                                    main = "Kaplan-Meier Overall Survival Curves",
                                    ylab = "Probability of survival",
                                    xlab = "Time since diagnosis (days)",
                                    filename = "survival.pdf",
                                    color = NULL,
                                    height = 8,
                                    width = 12,
                                    dpi = 300,
                                    pvalue = TRUE,
                                    conf.int = TRUE,
                                    barcode =NULL)
                                 
 {
  
  if (is.null(barcode)){
  
  
                TCGAanalyze_survival(clin.mm,
                                     clusterCol,
                                     legend,
                                     labels,
                                     risk.table,
                                     xlim,
                                     main,
                                     ylab,
                                     xlab,
                                     filename,
                                     color,
                                     height,
                                     width,
                                     dpi,
                                     pvalue,
                                     conf.int)
    
  }
  
  else{
    
    
    clin.mm.filt<-clin.mm[clin.mm$bcr_patient_barcode %in% barcode,]
    
                  TCGAanalyze_survival(clin.mm.filt,
                                       clusterCol,
                                       legend,
                                       labels,
                                       risk.table,
                                       xlim,
                                       main,
                                       ylab,
                                       xlab,
                                       filename,
                                       color,
                                       height,
                                       width,
                                       dpi,
                                       pvalue,
                                       conf.int)
    
    
    
  }
    
    
    
  
}