statisticsForPREDAfromEset: function to compute a statisticsForPREDA object from an...

Description Usage Arguments Details Value Author(s) See Also Examples

Description

function to compute a statisticsForPREDA object from an ExpressionSet object

Usage

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# statisticsForPREDAfromEset(.Object, pData_classColumn=NULL,
# statisticType=NULL, logged=TRUE, referenceGroupLabel=NULL,
# classVector=NULL, testedTail="both")

statisticsForPREDAfromEset(.Object, ...)

Arguments

.Object

Object of class ExpressionSet

...

See below

pData_classColumn:

Column from pData(.Object) containig the labels for different samples classes.

statisticType:

Stastistic for differential expression that is computed on input data. Possible values are "tstatistic", "FC" (Fold Change), "FCmedian" (fold change computed on medians)

logged:

Logical value (default TRUE) to specify if the input data are logged (Log2). This parameter will influence the computation of statistics.

referenceGroupLabel:

Specify which class label is used for the reference sample used in computing statistics for differential expression.

classVector:

If pData_classColumn is NULL then a vector specifying the sample classes is required and can be provided with classVector parameter

testedTail:

Specify what tail of the distribution will be tested for significantly extreme values in PREDA analysis. Possible values are "both", "upper" or "lower". Default value is "both".

Details

An object of class ExpressionSet is used as input and gene centered statistics for differential expression are computed on the contained data. The computed statistics are used to build a StatisticsForPREDA object

Value

An object of class StatisticsForPREDA

Author(s)

Francesco Ferrari

See Also

"StatisticsForPREDA"

Examples

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  ## Not run: 

require(PREDAsampledata)

data(ExpressionSetRCC)

GEstatisticsForPREDA<-statisticsForPREDAfromEset(
ExpressionSetRCC, statisticType="tstatistic",
referenceGroupLabel="normal", classVector=sampleinfo[,"Class"])

  
## End(Not run)

PREDA documentation built on May 6, 2019, 2:07 a.m.