Problem in Heat map generation of DE genes in Agilent Microarray data analysis
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8.8 years ago
Vinay Singh ▴ 50

Hello to all,

I have started agilent microarray data analysis (one color), I have used R bioconductor for analysis steps i used in are as follows now i am not able to get heatmap of differentially expressed genes . Please help me.

library(limma)

T <-readTargets("Targets.txt")

x <-read.maimages(targets, source="agilent",green.only=TRUE)
y <-backgroundCorrect(x, "normexp", offset=50)
y <-normalizeBetweenArrays(y, method="quantile")

y.ave <- avereps(y, ID=y$genes$ProbeName)

f <- factor(targets$Condition, levels = unique(targets$Condition))

design <- model.matrix(~0 + f)
colnames(design) <- levels(f)

fit <- lmFit(y.ave, design)

contrast.matrix <- makeContrasts("control-drought", "control-heat", "drought-control","control-combined","heat-drought", levels=design)

fit2 <- contrasts.fit(fit, contrast.matrix)
fit2 <- eBayes(fit2)

C.top<-as.numeric(rownames(topTable(fit2, coef=1,n=50)))

heatmap(y.ave$M[C.top,])
Error in heatmap(y.ave$M[C.top, ]) : 'x' must be a numeric matrix
R limma heatmap microarray analysis • 2.9k views
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Hints: what is C.top (it is not defined in the code example),

Your data to give to heatmap must be a numeric matrix (error message is obviously complaining 'it is not'). Output head(y.ave$M[C.top, ]), and you will see what the problem is.

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Sorry I have used this step here before heatmap that is
C.top<-as.numeric(rownames(topTable(fit2, coef=1,n=50)))
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And what about: head(y.ave$M[C.top, ]) ??

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Thanks Michael for paying attention to my problem actually I am a beginner in R I have just referred to the question. Please help me in generating heatmap of DE genes of microarray data.

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