bapred (version 0.2)

svaba: Batch effect adjustment using SVA

Description

Performs batch effect adjustment using Surrogate Variable Analysis (SVA) and additionally returns information necessary for addon batch effect adjustment with frozen SVA.

Usage

svaba(x, y, batch, nbf = NULL, algorithm = "fast")

Arguments

x

matrix. The covariate matrix. Observations in rows, variables in columns.

y

factor. Binary target variable. Currently has to have levels '1' and '2'.

batch

factor. Batch variable. Currently has to have levels: '1', '2', '3' and so on.

nbf

integer. Number of latent factors to estimate.

algorithm

character. If method = "fast" the "approximate fSVA algorithm" will be used in frozen SVA. If method = "exact" the "exact fSVA algorithm" will be used. See Parker et al. (2014).

Value

• svaba returns an object of class svatrain. An object of class "svatrain" is a list containing the following components:
• xadj
  matrix of adjusted (training) data
• xtrain
  the unadjusted covariate matrix. Used in frozen SVA.
• ytrain
  binary target variable. Used in frozen SVA.
• svobj
  output of the function sva(). Used in frozen SVA.
• algorithm
  algorithm to use in frozen SVA
• nbatches
  number of batches
• batch
  batch variable

Details

This is essentially a wrapper function of the function sva() from the Bioconductor package of the same name.

References

Leek, J. T., Storey, J. D. (2007) Capturing Heterogeneity in Gene Expression Studies by Surrogate Variable Analysis. PLoS Genetics, 3, 1724--1735. Parker, H. S., Bravo, H. C., Leek, J. T. (2014) Removing batch effects for prediction problems with frozen surrogate variable analysis. PeerJ, 2, e561.

Examples

data(autism)

# Random subset of 150 variables:
set.seed(1234)
Xsub <- X[,sample(1:ncol(X), size=150)]

# In cases of batches with more than 20 observations
# select 20 observations at random:
subinds <- unlist(sapply(1:length(levels(batch)), function(x) {
  indbatch <- which(batch==x)
  if(length(indbatch) > 20)
    indbatch <- sort(sample(indbatch, size=20))
  indbatch
}))
Xsub <- Xsub[subinds,]
batchsub <- batch[subinds]
ysub <- y[subinds]



params <- svaba(x=Xsub, y=ysub, batch=batchsub)