RankingFC {GeneSelector}R Documentation

Ranking based on the (log) foldchange

Description

Naive ranking that only considers difference in means without taking variances into account.
For S4 method information, see RankingFC-methods.

Usage

RankingFC(x, y, type = c("unpaired", "paired", "onesample"), 
          pvalues = TRUE, gene.names = NULL, LOG = FALSE, ...)

Arguments

x A matrix of gene expression values with rows corresponding to genes and columns corresponding to observations or 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 specifying the phenotype variable in the output from pData.
If type = paired, take care that the coding is analogously to the requirement concerning x
type
"unpaired":
two-sample test.
"paired":
paired test. Take care that the coding of y is correct (s. above)
"onesample":
y has only one level. Test whether the true mean is different from zero.

pvalues Should p-values be computed ? Defaults to TRUE.
gene.names An optional vector of gene names.
LOG By default, the data are assumed to be already logarithm-ed. If not, this can be done by setting LOG=TRUE
... Currently unused argument.

Value

An object of class GeneRanking

Note

Take care that the log foldchange is computed, therefore logarithmization might be necessary.
The p-values for the difference in means are based on a standard normal assumption.

Author(s)

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

See Also

GetRepeatRanking, RankingTstat, RankingWelchT, RankingWilcoxon, RankingBaldiLong, RankingFoxDimmic, RankingLimma, RankingEbam, RankingWilcEbam, RankingSam, RankingBstat, RankingShrinkageT, RankingSoftthresholdT, RankingPermutation, RankingGap

Examples

## Load toy gene expression data
data(toydata)
### class labels
yy <- toydata[1,]
### gene expression
xx <- toydata[-1,]
### run RankingFC
FC <- RankingFC(xx, yy, type="unpaired")

[Package GeneSelector version 1.2.0 Index]