Learn R Programming

RnBeads (version 1.4.0)

rnb.execute.sva: rnb.execute.sva

Description

Conduct Surrogate Variable Analysis (SVA) on the beta values of an RnBSet for given target variables

Usage

rnb.execute.sva(rnb.set, cmp.cols = rnb.getOption("inference.targets.sva"), columns.adj = rnb.getOption("covariate.adjustment.columns"), assoc = TRUE, numSVmethod = rnb.getOption("inference.sva.num.method"))

Arguments

rnb.set
The RnBSet object on which the SVA should be conducted
cmp.cols
a vector of sample annotation column names which will be the targets of the SVA.
columns.adj
Column names in the table of phenotypic information to be used for confounder adjustment.
assoc
a flag indicating whether association information with principal components and other sample annotation should be returned
numSVmethod
method to estimate the number of surrogate variables. Passed to sva.

Value

An object of class SvaResult: basically a list containing the following elements:
num.components
a vector storing the number of detected SVs for each target variable
sva.performed
a vector storing whether SVA was performed on a target variable and whether more than 0 SVs were found
targets
a vector storing the names of the target variables
components
a list storing for each target variable a matrox containing the sample-wise SVs as rows
assoc
a special object containing association information of SVs with principal components and sample annotations typically only used rnb.section.sva.

Examples

Run this code

library(RnBeads.hg19)
data(small.example.object)
logger.start(fname=NA)
sva.obj <- rnb.execute.sva(rnb.set.example,c("Sample_Group","Treatment"),numSVmethod="be")
sva.obj$sva.performed
sva.obj$num.components
rnb.set.mod <- set.covariates.sva(rnb.set.example, sva.obj)
has.covariates.sva(rnb.set.example,"Sample_Group")
has.covariates.sva(rnb.set.mod,"Sample_Group")
has.covariates.sva(rnb.set.mod,"Treatment")

Run the code above in your browser using DataLab