p.squared.t.test:

In shaileshtripathi/ssapbm: self-contained and competitive pathway-based methos (sub sample analysis of pathway-based methods.)

Usage

p.squared.t.test(data, cls1, cls2, steps = 100, sampling = "sample.labels", pathways = NULL)

Arguments

data
cls1
cls2
steps
sampling
pathways

Examples

##---- Should be DIRECTLY executable !! ----
##-- ==>  Define data, use random,
##--	or do  help(data=index)  for the standard data sets.

## The function is currently defined as
function (data, cls1, cls2, steps = 100, sampling = "sample.labels", 
    pathways = NULL) 
{
    tv <- squared.t.test(data, cls1, cls2, pathways = pathways)
    tvec <- resampling.squared.t.test(data, cls1, cls2, steps = steps, 
        pathways = pathways, sampling = sampling)
    tvec <- cbind(tv, tvec)
    pval <- apply(tvec, 1, function(x) {
        sum(x[2:(steps + 1)] > x[1])/steps
    })
    cbind(tv, pval)
  }

shaileshtripathi/ssapbm documentation built on May 29, 2019, 8:06 p.m.