bin_multitest: bin_multitest

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

Usage

bin_multitest(i, k, variable, select, testdata, testlevel, levs, position0, position1, method, psigalpha = 0.05)

Arguments

i
k
variable
select
testdata
testlevel
levs
position0
position1
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, variable, select, testdata, testlevel, levs, 
    position0, position1, method, psigalpha = 0.05) 
{
    group <- testdata[[variable]]
    n1 <- length(position0)
    n2 <- length(position1)
    group[sample(position0, k)] <- levs[2]
    group[sample(position1, k)] <- levs[1]
    group <- factor(group)
    if (method == "kruskal") {
        otu.test <- apply(testlevel, 2, function(x) {
            kt <- kruskal.test(x = x, g = group)
            return(data.frame(pv = kt$p.value, es = kt$statistic/sqrt(n1^2 + 
                n2^2)))
        })
        otu.test <- do.call(rbind, otu.test)
    }
    else if (method == "wilcox") {
        otu.test <- apply(testlevel, 2, function(x) {
            wt <- wilcox.test(x ~ group)
            return(data.frame(pv = wt$p.value, es = wt$statistic/sqrt(n1^2 + 
                n2^2)))
        })
        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
    effectsize <- effectsize[select]
    return(list(psig = psig, pvalue = pvalue, effectsize = effectsize))
  }

LyonsZhang/ProgPerm documentation built on July 16, 2020, 12:45 a.m.