MiSPU-package: Microbiome Based Sum of Powered Score (MiSPU) Tests

In MiSPU: Microbiome Based Sum of Powered Score (MiSPU) Tests

Description

There is an increasing interest in investigating how the compositions of microbial communities are associated with human health and disease. In this package, we present a novel global testing method called aMiSPU, that is highly adaptive and thus high powered across various scenarios, alleviating the issue with the choice of a phylogenetic distance. Our simulations and real data analysis demonstrated that aMiSPU test was often more powerful than several competing methods while correctly controlling type I error rates.

Details

Package:	MiSPU
Type:	Package
Version:	1.0
Date:	2016-02-29
License:	GPL-2

Author(s)

Chong Wu, Wei Pan Maintainer: Chong Wu <[e-mail]>

References

Pan, W., et al.(2014) A powerful and adaptive association test for rare variants, Genetics, 197(4), 1081-95

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

Example output

Loading required package: vegan
Loading required package: permute
Loading required package: lattice
This is vegan 2.4-4
Loading required package: ape
Loading required package: aSPU
Loading required package: gee
Loading required package: MASS
Loading required package: mvtnorm
Loading required package: fields
Loading required package: spam
Loading required package: dotCall64
Loading required package: grid
Spam version 2.1-1 (2017-07-02) is loaded.
Type 'help( Spam)' or 'demo( spam)' for a short introduction 
and overview of this package.
Help for individual functions is also obtained by adding the
suffix '.spam' to the function name, e.g. 'help( chol.spam)'.

Attaching package: 'spam'

The following objects are masked from 'package:base':

    backsolve, forwardsolve

Loading required package: maps
Loading required package: matrixStats
Loading required package: cluster

Attaching package: 'cluster'

The following object is masked from 'package:maps':

    votes.repub

$Unweighted
$Unweighted$Ts
      SPU2       SPU3       SPU4       SPU5       SPU6       SPU7       SPU8 
 4.7298495 -0.3944415  0.6027891 -0.2832744  0.2744694 -0.1910116  0.1604917 
    SPUInf       aSPU 
 0.7930445  0.0190000 

$Unweighted$pvs
      SPU2       SPU3       SPU4       SPU5       SPU6       SPU7       SPU8 
0.01900000 0.21400000 0.03900000 0.05300000 0.04100000 0.04400000 0.04200000 
    SPUInf       aSPU 
0.04100000 0.03796204 


$Weighted
$Weighted$Ts
         SPU2          SPU3          SPU4          SPU5          SPU6 
 8.816789e-03 -1.452608e-04  9.389882e-06 -4.534595e-07  2.477021e-08 
         SPU7          SPU8        SPUInf          aSPU 
-1.318319e-09  7.110702e-11  5.387574e-02  1.000000e-03 

$Weighted$pvs
       SPU2        SPU3        SPU4        SPU5        SPU6        SPU7 
0.014000000 0.003000000 0.003000000 0.001000000 0.001000000 0.001000000 
       SPU8      SPUInf        aSPU 
0.001000000 0.001000000 0.001998002 


$aMiSPU
$aMiSPU$Ts
[1] 0.001

$aMiSPU$pvalue
[1] 0.002997003

MiSPU documentation built on May 1, 2019, 8:41 p.m.