ranking {MiSPU}

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.

Author(s)

Chong Wu

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)