Global tests for expression data of high-dimensional sets of molecular features.

Description

Global tests for expression data of high-dimensional sets of molecular features.

Details

Global tests for expression data of high-dimensional sets of molecular features.

Author(s)

Klaus Jung Klaus.Jung@ams.med.uni-goettingen.de

Examples

### Global comparison of a set of 100 genes between two experimental groups.
X1 = matrix(rnorm(1000, 0, 1), 10, 100)
X2 = matrix(rnorm(1000, 0.1, 1), 10, 100)
RHD = RepeatedHighDim(X1, X2, paired=FALSE)
summary(RHD)

### Global comparison of a set of 100 proteins between two experimental groups,
### where (tau * 100) percent of expression levels are missing.
n1 = 10
n2 = 10
d = 100
tau = 0.1
X1 = t(matrix(rnorm(n1*d, 0, 1), n1, d))
X2 = t(matrix(rnorm(n2*d, 0.1, 1), n2, d))
X1[sample(1:(n1*d), tau * (n1*d))] = NA
X2[sample(1:(n2*d), tau * (n2*d))] = NA
GlobTestMissing(X1, X2, nperm=100)

Results

R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

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> library(RepeatedHighDim)
Loading required package: MASS
Loading required package: nlme
> png(filename="/home/ddbj/snapshot/RGM3/R_CC/result/RepeatedHighDim/RepeatedHighDim-package.Rd_%03d_medium.png", width=480, height=480)
> ### Name: RepeatedHighDim-package
> ### Title: Global tests for expression data of high-dimensional sets of
> ###   molecular features.
> ### Aliases: RepeatedHighDim-package
> ### Keywords: package
> 
> ### ** Examples
> 
> ### Global comparison of a set of 100 genes between two experimental groups.
> X1 = matrix(rnorm(1000, 0, 1), 10, 100)
> X2 = matrix(rnorm(1000, 0.1, 1), 10, 100)
> RHD = RepeatedHighDim(X1, X2, paired=FALSE)
> summary(RHD)
Number of Genes: 10 
Number of Samples in Group 1: 100 
Number of Samples in Group 2: 100 
Samples are Paired: FALSE 

  effect      F     df1      df2      p
1  Group 1.6758 10.1206 2002.176 0.0798
> 
> ### Global comparison of a set of 100 proteins between two experimental groups,
> ### where (tau * 100) percent of expression levels are missing.
> n1 = 10
> n2 = 10
> d = 100
> tau = 0.1
> X1 = t(matrix(rnorm(n1*d, 0, 1), n1, d))
> X2 = t(matrix(rnorm(n2*d, 0.1, 1), n2, d))
> X1[sample(1:(n1*d), tau * (n1*d))] = NA
> X2[sample(1:(n2*d), tau * (n2*d))] = NA
> GlobTestMissing(X1, X2, nperm=100)
$pval
[1] 0.83

> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>