batchAdjust {PAA} | R Documentation

## Adjust microarray data for batch effects.

### Description

Adjusts `EListRaw` or `EList` data for batch/lot effects.

### Usage

    batchAdjust(elist=NULL, log=NULL)

### Arguments

`elist` | `EList` or `EListRaw` object containing the data to be adjusted (mandatory).
`log` | logical indicating whether the data is in log scale (mandatory; note: if TRUE log2 scale is expected).

### Details

This is a wrapper to `sva`'s function `ComBat()` for batch adjustment using the empirical Bayes approach. To use batchAdjust the targets information of the `EList` or `EListRaw` object must contain the columns `"Batch"` (containing batch/lot information for each particular array) and `"Group"` (containing experimental group information for each particular array).

### Value

An `EListRaw` or `EList` object with the adjusted data in log scale is returned.

### Note

The targets information of the `EListRaw` or `EList` object must contain the columns `"Batch"` and `"Group"`.

### Author(s)

Michael Turewicz, michael.turewicz@rub.de

### References

The package `sva` by Jeffrey T. Leek et al. can be downloaded from Bioconductor (http://www.bioconductor.org/).

Johnson WE, Li C, and Rabinovic A (2007) Adjusting batch effects in microarray expression data using empirical Bayes methods. Biostatistics 8:118-27.

### Examples

    cwd <- system.file(package="PAA")
    load(paste(cwd, "/extdata/Alzheimer.RData", sep=""))
    elist <- elist[elist$genes$Block < 10,]
    elist <- batchAdjust(elist=elist, log=FALSE)

[Package PAA version 1.14.0 Index]