bga.jackknife {made4} | R Documentation

## Jackknife between group analysis

### Description

Performs one-leave-out jackknife analysis of a between group analysis as described by Culhane et al., 20002

### Usage

    bga.jackknife(data, classvec, ...)

### Arguments

`data` | Input dataset. A `matrix`, `data.frame` If the input is gene expression data in a `matrix` or `data.frame`. The columns contain the cases (array samples) which will be jackknifed.
`classvec` | A factor or vector which describes the classes in the training dataset
`...` | further arguments passed to or from other methods

### Details

Performs a one-leave-out cross validation of between group analysis `bga`. Input is a training dataset. This can take 5-10 minutes to compute on standard data gene expression matrix.

In jackknife one leave out analysis, one case (column) is removed. The remaining dataset is subjected to `bga`. Then the class of the case that was removed is predicted using `suppl`. This analysis is repeated until all samples have been removed and predicted.

### Value

A list containing

`results` | The projected co-ordinates of each sample
`summary` | A summary of number and percentage of correctly assigned samples

### Author(s)

Aedin Culhane

### References

Culhane et al., 2002 Between-group analysis of microarray data. Bioinformatics. 18(12):1600-8.

### See Also

See Also `bga`, `bga.suppl`, `suppl`,`bga`, `bca`, `plot.bga`

### Examples

    data(khan)
    # NOTE using a very reduced dataset (first 5 genes) to speed up results
    # hence expect poor prediction accuracy
    dim(khan$train)
    print("using only small subset of data")
    if (require(ade4, quiet = TRUE)) {
    bga.jackknife(khan$train[1:5,], khan$train.classes) }

[Package made4 version 1.64.0 Index]