MiSPU (version 1.0)

ranking: ranking the OTUs

Description

Ranking the importance of each taxa.

Usage

ranking(y, X, tree, cov = NULL,gamma,g.taxon.index,model = "binomial")

Arguments

y

Outcome of interest. It can be a disease indicator; =0 for controls, =1 for cases. Or it can be a quantitative trait. A vector with length n (number of observations).

X

OTU count table, row - n sample, column - q OTU

tree

Rooted phylogenetic tree of R class “phylo”

cov

Covariates. A matrix with dimension n by p (n :number of observation, p : number of covariates).

gamma

The best gamma selected by aMiSPU test.

g.taxon.index

g.taxon.index = 1 stands for weigted generalized taxon proportion; otherwise means unweighted generalized taxon proportion.

model

Use "gaussian" for a quantitative trait, and use "binomial" for a binary trait.

Value

A matrix containing the ranking score, the higher the more important.

References

Chong, W., Pan, W. (2015) An Adaptive Association Test for Microbiome Data, submitted.

Examples

data(throat.otu.tab)
data(throat.tree)
data(throat.meta)

Y.tmp =throat.meta[,3]
Y = rep(0,dim(throat.meta)[1])
Y[Y.tmp=="Smoker"] = 1

cov.tmp = throat.meta[,c(10,12)]
cov = matrix(1,dim(throat.meta)[1],2)
cov[cov.tmp[,1]== "None",1] = 0
cov[cov.tmp[,2]== "Male",2] = 0

start.time = proc.time()
X = as.matrix(throat.otu.tab)

#out = MiSPU(Y,X, throat.tree,cov,model =  "binomial", pow = c(2:8, Inf), n.perm = 1000)
out = ranking(Y,X, throat.tree,cov,gamma = 2, g.taxon.index =1)