interactionResult-class {ArrayTools}R Documentation

Class to Contain the Regression Result Based on An Interaction Model

Description

Class to Contain the Regression Result Based on An Interaction Model. Interaction is a statistical term refering to a situation when the relationship between the outcome and the variable of the main interest differs at different levels of the extraneous variable

Creating Objects

interactionResult object is generally created from the postInteraction function See postInteraction

Object Components

A list of four or more components. Each component is a reggressResult class. The first component contains all the genes. The second component contains genes with the interaction effect The rest components contains genes with the interaction effect across different levels. Each component contains the result for each level.

Extends

Class "list", from data part. Class "vector", by class "list", distance 2.

Methods

adjustment
signature(object = "regressResult")
{: access the adjustment slot }
getAdjP
signature(object = "regressResult")
{: access the adjPVal slot }
getAnnotation
signature(object = "regressResult")
{: access the annotation slot }
getContrast
signature(object = "regressResult")
{: access the contrast slot }
getF
signature(object = "regressResult")
{: access the FValue slot}
getFC
signature(object = "regressResult")
{: access the foldChange slot }
getFCCutoff
signature(object = "regressResult")
{: access the significantFCCutoff slot}
getFileName
signature(object = "regressResult")
{: access the fileName slot }
getFilterMethod
signature(object = "regressResult")
{: access the filterMethod slot }
getID
signature(object = "regressResult")
{: access the ID slot }
getIndex
signature(object = "regressResult")
{: access the significantIndex slot}
getNormalizationMethod
signature(object = "regressResult")
{: access the normalizationMethod slot}
getP
signature(object = "regressResult")
{: access the pValue slot }
getPCutoff
signature(object = "regressResult")
{: access the significantPvalueCutoff slot }
Output2HTML
signature(object = "regressResult")
{: create HTML file for sigificant genes in regressionResult}
regressionMethod
signature(object = "regressResult")
{: access the regressionMethod slot}
selectSigGene
signature(object = "regressResult")
{: select significant genes for regressionResult class}
show
signature(object = "regressResult")
{: print regressResult}
Sort
signature(x = "regressResult")
{: sort regressResult}
summary
signature(object = "regressResult")
{: print the summary for regressResult}
getLength
signature(object = "interactionResult")
{: calculate the length of the interactionResult class}

Author(s)

Xiwei Wu, Arthur Li

See Also

regressResult

Examples

## Creating the interactionREsult takes a few steps:
data(eSetExample)
design.int<- new("designMatrix", target=pData(eSetExample), covariates = c("Treatment", "Group"),
    intIndex = c(1, 2))
contrast.int<- new("contrastMatrix", design.matrix = design.int, interaction=TRUE)
result.int<- regress(eSetExample, contrast.int)
sigResult.int <- selectSigGene(result.int)
intResult <- postInteraction(eSetExample, sigResult.int, mainVar ="Treatment",
   compare1 = "Treated", compare2 = "Control")

[Package ArrayTools version 1.2.1 Index]