Summary of RepeatedHighDim function

Description

Summarizes the test results obtained by the RepeatedHighDim function.

Usage

  ## S3 method for class 'RHD'
 summary(object, ...)

Arguments

Value

No value

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)

R is free software and comes with ABSOLUTELY NO WARRANTY.
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Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(RepeatedHighDim)
Loading required package: MASS
Loading required package: nlme
> png(filename="/home/ddbj/snapshot/RGM3/R_CC/result/RepeatedHighDim/summary.RHD.Rd_%03d_medium.png", width=480, height=480)
> ### Name: summary.RHD
> ### Title: Summary of RepeatedHighDim function
> ### Aliases: summary.RHD
> 
> ### ** 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 0.9827 9.9846 1955.033 0.4562
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>