SWAP.Filter.Wilcoxon: Statistical feature filtering based on Wilcoxon test on the...

In switchBox: Utilities to train and validate classifiers based on pair switching using the K-Top-Scoring-Pair (KTSP) algorithm

Description

SWAP.Filter.Wilcoxon filters the features to top differential expressed to be used for KTSP classifier implementation.

Usage

SWAP.Filter.Wilcoxon(phenoGroup, inputMat, featureNo = 100, UpDown = TRUE)

Arguments

phenoGroup	a factor with levels containing training labels for the phenotype of interest.
inputMat	a numerical matrix containing feature measurements to be used to implement the classifier (e.g., the set of gene expression values). The columns of this matrix correspond to samples and must correspond to phenoGroup. The rows represent the features and rownames(inputMat) will be used as feature names.
featureNo	an integer specifying the number of different features to be returned.
UpDown	logical value specifying whether an equal proportion of features displaying opposite change across the two phenotypes should be returned (e.g.an equal number of up- and down-regulated genes).

Value

The names of the features that survived the statistical filtering, i.e. differential expressed features.

Author(s)

Bahman Afsari [e-mail], Luigi Marchionni [e-mail]

References

See switchBox for the references.

See Also

SWAP.KTSP.Classify, SWAP.Filter.Wilcoxon, SWAP.CalculateSignedScore

Examples

### Load gene expression data for the training set
data(trainingData)

### Return equal numbers of up- and down- regulated features (default)
SWAP.Filter.Wilcoxon(trainingGroup, matTraining, featureNo=10)

### Return the top 10 differentially expressed features irrispective to
### the direction of change.
### By setting the argument 'UpDown' equal to FALSE the number of
### up- and down- regulated features can be different
SWAP.Filter.Wilcoxon(trainingGroup, matTraining, featureNo=10, UpDown=FALSE)

switchBox documentation built on Nov. 8, 2020, 5:43 p.m.