batchFilter.anova {PAA} | R Documentation

## Remove features which are differential regarding microarray batches / lots in a multi-batch scenario.

### Description

Finds features which are differential regarding at least two microarray batches / lots in a multi-batch scenario (i.e., > 2 batches) via one-way analysis of variance (ANOVA) and removes them.

### Usage

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

### Arguments

`elist` | `EList` or `EListRaw` object (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) to find features which are differential regarding at least two microarray batches / lots in a multi-batch scenario (i.e., more than two batches). For this purpose, thresholds for p-values obtained from an one-way analysis of variance (ANOVA) 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 at least two microarray batches / lots.

### Author(s)

Ivan Grishagin (Rancho BioSciences LLC, San Diego, CA, USA), John Obenauer (Rancho BioSciences LLC, San Diego, CA, USA) and Michael Turewicz (Ruhr-University Bochum, Bochum, Germany), michael.turewicz@rub.de

### Examples

    cwd <- system.file(package="PAA")
    load(paste(cwd, "/extdata/Alzheimer.RData", sep=""))
    elist <- elist[elist$genes$Block < 10,]
    elist <- batchFilter.anova(elist=elist, log=FALSE, p.thresh=0.001,
     fold.thresh=3)

[Package PAA version 1.20.0 Index]