con_multitest: con_multitest

In LyonsZhang/ProgPermute: Progressive permutation for a dynamic representation of the robustness of microbiome discoveries

Usage

con_multitest(i, k, n, variable, select, testdata, testlevel, method, psigalpha = 0.05)

Arguments

i
k
n
variable
select
testdata
testlevel
method
psigalpha

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 (i, k, n, variable, select, testdata, testlevel, method, 
    psigalpha = 0.05) 
{
    group <- testdata[[variable]]
    indx <- 1:n
    indx0 <- sample(indx, n - k)
    indx1 <- indx[!indx %in% indx0]
    group[indx1] <- group[sample(indx1)]
    otu.test <- apply(testlevel, 2, function(x) {
        ct <- cor.test(x = x, y = group, method = method)
        return(data.frame(pv = ct$p.value, es = ct$statistic, 
            cr = ct$estimate))
    })
    otu.test <- do.call(rbind, otu.test)
    psig <- sum(!otu.test$pv > psigalpha, na.rm = T)
    pvalue <- -log10(otu.test$pv[select])
    effectsize <- otu.test$es[select]
    correlation <- otu.test$cr[select]
    return(list(psig = psig, pvalue = pvalue, effectsize = effectsize, 
        correlation = correlation))
  }

LyonsZhang/ProgPermute documentation built on July 22, 2020, 4:09 p.m.