computeLogRatio(e, reference, within = NULL, across = NULL, nReplicatesVar = 3, ...)
reference$var
and across
variables will be
compared to the reference group. Two different approaches to obtain necessary computations:
reference=list(var = 'boolean', level = 1),
across = c('compound','dose')
}
pData(e)['refvar'] <- paste(pData(e)['compound'], pData(e)['dose'],sep='.')
so as to use reference = list(var = 'refvar', level ='comp1.dose1')
as argument for reference.}plotLogRatio
if (require(ALL)){
data(ALL, package = "ALL")
ALL <- addGeneInfo(ALL)
ALL$BTtype <- as.factor(substr(ALL$BT,0,1))
ALL2 <- ALL[,ALL$BT != 'T1'] # omit subtype T1 as it only contains one sample
ALL2$BTtype <- as.factor(substr(ALL2$BT,0,1)) # create a vector with only T and B
# Test for differential expression between B and T cells
tTestResult <- tTest(ALL, "BTtype", probe2gene = FALSE)
topGenes <- rownames(tTestResult)[1:20]
# plot the log ratios versus subtype B of the top genes
LogRatioALL <- computeLogRatio(ALL2, reference=list(var='BT',level='B'))
a <- plotLogRatio(e=LogRatioALL[topGenes,],openFile=FALSE, tooltipvalues=FALSE, device='X11',
colorsColumnsBy=c('BTtype'), main = 'Top 20 genes most differentially between T- and B-cells',
orderBy = list(rows = "hclust"),
probe2gene = TRUE)
}
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