TCGAbiolinks (version 1.0.10)

TCGAanalyze_survival: 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, cutoff = 0, main = "Kaplan-Meier Overall Survival Curves", ylab = "Probability of survival", xlab = "Time since diagnosis (days)", filename = "survival.pdf", color = NULL, height = 8, width = 12, print.value = 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

cutoff

xlim This parameter will be a limit in the x-axis. That means, that patients with days_to_deth > cutoff will be set to Alive.

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 of the lines.

height

Image height

width

Image width

print.value

Print pvalue in the plot? Default: TRUE

Value

Survival plot

Examples

days_to_death <- floor(runif(200, 1, 1000))
vital_status <- c(rep("Dead",200))
groups <- c(rep(c("G1","G2"),c(100,100)))
df <- data.frame(days_to_death,vital_status,groups)
TCGAanalyze_survival(df,clusterCol="groups")
## Not run: 
# clinical <- TCGAquery_clinic("gbm","clinical_patient")
# TCGAanalyze_survival(clinical,"gender", filename = "surv.pdf", legend="Gender")
# ## End(Not run)