seeCov {DExMA}R Documentation

Visualization the effect of covariates in data variability

Description

It uses the prince and prince.plot function from the swamp package to visualiza the effect of covariates in data variability

Usage

seeCov(expressionMatrix, pheno)

Arguments

expressionMatrix

A matrix or data frame with genes in rows and samples in columns. An ExpressionSet object can be used too

pheno

A dataframe with samples in rows and covariates in colums. It should contain only the most important covariates

Value

A visualization (heatmap) in which it can be seen how the data variability is affected by the covariates. The plot represents the p-values of each principal component associated with the covariates.

Note

Requires the package swamp

Author(s)

Juan Antonio Villatoro Garcia, juanantoniovillatorogarcia@gmail.com

References

Martin Lauss (2019). swamp: Visualization, Analysis and Adjustment of High-Dimensional Data in Respect to Sample Annotations. R package version 1.5.1. https://CRAN.R-project.org/package=swamp

See Also

batchRemove

Examples

data(DExMAExampleData)
seeCov(listMatrixEX$Study2, listPhenodatas$Study2)


[Package DExMA version 1.1.2 Index]