tnsKM-methods: Kaplan-Meier analysis for TNS class objects

In csgroen/RTNsurvival: Survival analysis using transcriptional networks inferred by the RTN package

Description

Creates survival curves and tests if there is a difference between curves using 'survfit' and 'survdiff' functions, respectivelly.

Usage

## S4 method for signature 'TNS'
tnsKM(tns, regs = NULL, nSections = 1,
  verbose = TRUE)

Arguments

tns	A TNS object, which must have passed GSEA2 analysis.
regs	An optional string vector listing regulons to be tested.
nSections	A numeric value for sample stratification. The larger the number, the more subdivisions will be created for the Kaplan-Meier analysis.
verbose	A logical value specifying to display detailed messages (when verbose=TRUE) or not (when verbose=FALSE).

Value

Results from 'survfit' and 'survdiff', including log-rank statistics.

Examples

# load survival data
data(survival.data)

# load TNI-object
data(stni, package = "RTN")

stns <- tni2tnsPreprocess(stni, survivalData = survival.data, 
        keycovar = c('Grade','Age'), time = 1, event = 2)
stns <- tnsGSEA2(stns)
stns <- tnsKM(stns)
tnsGet(stns, "kmTable")

csgroen/RTNsurvival documentation built on May 20, 2019, 1:49 p.m.