selectSigGeneInt(ArrayTools)
selectSigGeneInt()所属R语言包:ArrayTools
select differentially expressed genes from the interactionResult class
选择差异表达基因从interactionResult类
译者:生物统计家园网 机器人LoveR
描述----------Description----------
select differentially expressed genes based on p value and/or fold change from the interactionResult class
根据P值和/或倍从interactionResult类变化,选择差异表达的基因
用法----------Usage----------
selectSigGeneInt(object, pGroup = 0.05, fcGroup = 0, pMain = 0.05, fcMain = 0)
参数----------Arguments----------
参数:object
an interactionResult class
一个interactionResult类
参数:pGroup
the p value that used to select significant genes at each level of the covariate
p值,用来选择在每个协变量的水平显着的基因
参数:fcGroup
the fold change value that used to select significant genes at each level of the covariate
褶皱的变化值,用来选择在每个协变量的水平显着的基因
参数:pMain
the p values that used to select significant genes among genes without any interaction effect
p值选择基因之间没有任何互动效应显着的基因
参数:fcMain
the fold change values that used to select significant genes among genes without any interaction effect
褶皱的变化值,选择基因之间没有任何互动效应显着的基因
值----------Value----------
an interactionResult
1 interactionResult
作者(S)----------Author(s)----------
Xiwei Wu, Arthur Li
举例----------Examples----------
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")
sigResultInt <- selectSigGeneInt(intResult)
转载请注明:出自 生物统计家园网(http://www.biostatistic.net)。
注:
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