batchFilter {PAA} | R Documentation

## Remove differential features regarding array batches/lots.

### Description

Finds differential features regarding array batches/lots and removes them.

### Usage

    batchFilter(elist=NULL, lot1=NULL, lot2=NULL, log=NULL, p.thresh=0.05,
    fold.thresh=1.5, output.path=NULL)

### Arguments

`elist` | `EList` or `EListRaw` object (mandatory).
`lot1` | vector of column names for group 1 (mandatory).
`lot2` | vector of column names for group 2 (mandatory).
`log` | logical indicating whether the data is in log scale (mandatory; note: if TRUE log2 scale is expected).
`p.thresh` | positive float number between 0 and 1 indicating the maximum Student's t-test p-value for features to be considered as differential (e.g., `"0.5"`).
`fold.thresh` | float number indicating the minimum fold change for features to be considered as differential (e.g., `"1.5"`).
`output.path` | string indicating a path for saving results (optional).

### Details

This function takes an `EList` or `EListRaw` object (see `limma` documentation) and the batch-specific column name vectors `lot1` and `lot2` to find differential features regarding batches/lots. For this purpose, thresholds for p-values (Student's t-test) and fold changes can be defined. To visualize the differential features a volcano plot is drawn. Then, differential features are removed and the remaining data are returned. When an output path is defined (via `output.path`) volcano plots and result files are saved on the hard disk.

### Value

An `EList` or `EListRaw` object without differential features regarding array batches/lots.

### Author(s)

Michael Turewicz, michael.turewicz@rub.de

### Examples

    cwd <- system.file(package="PAA")
    load(paste(cwd, "/extdata/Alzheimer.RData", sep=""))
    elist <- elist[elist$genes$Block < 10,]
    lot1 <- elist$targets[elist$targets$Batch=='Batch1','ArrayID']
    lot2 <- elist$targets[elist$targets$Batch=='Batch2','ArrayID']
    elist <- batchFilter(elist=elist, lot1=lot1, lot2=lot2, log=FALSE,
      p.thresh=0.001, fold.thresh=3)

[Package PAA version 1.24.0 Index]