RHighDim: Detection of global group effect

In RepeatedHighDim: Methods for High-Dimensional Repeated Measures Data

Detection of global group effect

Description

Detection of global group effect

Usage

RHighDim(X1, X2, paired = TRUE)

Arguments

X1	Matrix of expression levels in first group. Rows represent features, columns represent samples.
X2	Matrix of expression levels in second group. Rows represent features, columns represent samples.
paired	FALSE if samples are unpaired, TRUE if samples are paired.

Details

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

Value

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

Author(s)

Klaus Jung

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. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1093/bioinformatics/btr152")}

See Also

For more information, please refer to the package's documentation and the tutorial: https://software.klausjung-lab.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 = RHighDim(X1, X2, paired=FALSE)
summary_RHD(RHD)

RepeatedHighDim documentation built on April 15, 2025, 1:28 a.m.