Detection of global group effect

Description

Global test for a set of molecular features (e.g. genes, proteins,...) between two experimental groups. Paired or unpaired design is allowed.

Usage

  RepeatedHighDim(X1, X2, paired = TRUE)

Arguments

Value

An object that contains the test results. Contents can be displayed by the summary function.

Author(s)

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

References

• Brunner, E (2009) Repeated measures under non-sphericity. Proceedings of the 6th St. Petersburg Workshop on Simulation, 605-609.

• Jung K, Becker B, Brunner B and Beissbarth T (2011) Comparison of Global Tests for Functional Gene Sets in Two-Group Designs and Selection of Potentially Effect-causing Genes. Bioinformatics, 27: 1377-1383.

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)

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.Rd_%03d_medium.png", width=480, height=480)
> ### Name: RepeatedHighDim
> ### Title: Detection of global group effect
> ### Aliases: RepeatedHighDim
> 
> ### ** 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 1.5177 9.978 1983.459 0.1269
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>