rnb.execute.sva {RnBeads} | R Documentation |
Conduct Surrogate Variable Analysis (SVA) on the beta values of an RnBSet for given target variables
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"))
rnb.set |
The |
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 |
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
.
Fabian Mueller
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")