TCGAanalyze_survival {TCGAbiolinks} | R Documentation

## Creates survival analysis

### Description

Creates a survival plot from TCGA patient clinical data using survival library. It uses the fields days_to_death and vital, plus a columns for groups.

### Usage

    TCGAanalyze_survival(
      data,
      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,
      ...
    )

### Arguments

`data` | TCGA Clinical patient with the information days_to_death
`clusterCol` | Column with groups to plot. This is a mandatory field, the caption will be based in this column
`legend` | Legend title of the figure
`labels` | labels of the plot
`risk.table` | show or not the risk table
`xlim` | x axis limits e.g. xlim = c(0, 1000). Present narrower X axis, but not affect survival estimates.
`main` | main title of the plot
`ylab` | y axis text of the plot
`xlab` | x axis text of the plot
`filename` | The name of the pdf file.
`color` | Define the colors/Pallete for lines.
`height` | Image height
`width` | Image width
`dpi` | Figure quality
`pvalue` | show p-value of log-rank test
`conf.int` | show confidence intervals for point estimates of survival curves.
`...` | Further arguments passed to ggsurvplot.

### Value

Survival plot

### Examples

     # clin <- GDCquery_clinic("TCGA-BRCA","clinical")
     clin <- 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))
     )
    TCGAanalyze_survival(clin, clusterCol="gender")
    TCGAanalyze_survival(clin, clusterCol="gender", xlim = 1000)
    TCGAanalyze_survival(clin,
                         clusterCol="gender",
                         risk.table = FALSE,
                         conf.int = FALSE,
                         color = c("pink","blue"))
    TCGAanalyze_survival(clin,
                         clusterCol="gender",
                         risk.table = FALSE,
                         xlim = c(100,1000),
                         conf.int = FALSE,
                         color = c("Dark2"))

[Package TCGAbiolinks version 2.22.4 Index]