| interactionResult-class {ArrayTools} | R Documentation |
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
interactionResult object is generally created from the postInteraction function
See postInteraction
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.
Class "list", from data part.
Class "vector", by class "list", distance 2.
signature(object = "regressResult")adjustment slot }
signature(object = "regressResult")adjPVal slot }
signature(object = "regressResult")annotation slot }
signature(object = "regressResult")contrast slot }
signature(object = "regressResult")FValue slot}
signature(object = "regressResult")foldChange slot }
signature(object = "regressResult")significantFCCutoff slot}
signature(object = "regressResult")fileName slot }
signature(object = "regressResult")filterMethod slot }
signature(object = "regressResult")ID slot }
signature(object = "regressResult")significantIndex slot}
signature(object = "regressResult")normalizationMethod slot}
signature(object = "regressResult")pValue slot }
signature(object = "regressResult")significantPvalueCutoff slot }
signature(object = "regressResult")signature(object = "regressResult")regressionMethod slot}
signature(object = "regressResult")regressionResult class}
signature(object = "regressResult")regressResult}
signature(x = "regressResult")regressResult}
signature(object = "regressResult")regressResult}
signature(object = "interactionResult")Xiwei Wu, Arthur Li
## 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")