GenerateFoldMatrix {GeneSelector}R Documentation

Altered datasets via k-Jackknife or Label (class) exchange

Description

Generates an object of class FoldMatrix that is then processed by GetRepeatRanking

Usage

GenerateFoldMatrix(x, y, k = 1, replicates = ifelse(k==1, ncol(x), 10), type = c("unpaired", "paired", "onesample"), minclassize = 2, balanced = FALSE, control)

Arguments

x A matrix of gene expression values with rows corresponding to genes and columns corresponding to observations.
Can alternatively an object of class ExpressionSet.
If type = paired, the first half of the columns corresponds to the first measurements and the second half to the second ones. For instance, if there are 10 observations, each measured twice, stored in an expression matrix expr, then expr[,1] is paired with expr[,11], expr[,2] with expr[,12], and so on.
y If x is a matrix, then y may be a numeric vector or a factor with at most two levels.
If x is an ExpressionSet, then y is a character specifyig the phenotype variable in the output from pData.
If type = paired, take care that the coding is analogously to the requirement concerning x
k Number of observations that are removed or whose labels are exchanged. Label exchange means that the actual label is replaced by the label of the other class (s. GetRepeatRanking).
replicates Number of replications if k>1.
type One of "paired", "unpaired", "onesample", depends on the type of test to be performed, s. for example RankingTstat.
minclassize If minclassize=k for some integer k, then the number of observations in each class are grater then or equal to minclassize for each replication.
balanced If balanced=TRUE, then the proportions of the two classes are (at least approximately) the same for each replication. It is a shortcut for a certain value of minclasssize. May not reasonable, if class proportions are unbalanced.
control Further control arguments concerning the generation process of the fold matrix, s. samplingcontrol.

Value

An object of class FoldMatrix.

warning

If the generation process (partially) fails, try to reduce the constraints or change the argument control.

Note

No jackknif-ed dataset will occur more than once, i.e. each replication is unique.

Author(s)

Martin Slawski martin.slawski@campus.lmu.de
Anne-Laure Boulesteix http://www.slcmsr.net/boulesteix

References

Davison, A.C., Hinkley, D.V. (1997)
Bootstrap Methods and their Application. Cambridge University Press

See Also

GenerateBootMatrix, GetRepeatRanking

Examples

 ## Load toy gene expression data
data(toydata)
### class labels
yy <- toydata[1,]
### gene expression
xx <- toydata[-1,]
### Generate Leave-One-Out / Exchange-One-Label matrix
loo <- GenerateFoldMatrix(xx, yy, k=1)
### A more complex example
l3o <- GenerateFoldMatrix(xx, yy, k=3, replicates=30, minclassize=5) 

[Package GeneSelector version 1.2.0 Index]