[BioC] Using gene symbols as labels for heatmap instead of microarray ID

António Brito Camacho toinobc at gmail.com
Thu Dec 19 03:04:34 CET 2013


Dear all,

I am trying to analyze a publicly available dataset from GEO and I would like to put in the heatmap row labels the more “human readable” , Gene Symbols instead of the chip “ID” .
I am aware that the function heatmap.2 accepts a parameter "labRow “, but I am not able to access the values in the fvarLabel “Gene Symbol”. Can someone help me?
The code that I have cobbled together from some websites and that i am using is the following:

library(limma)
library(GEOquery)
library(gplots)

#get the GEO dataset, the authors mention that the expression values are already normalized using systematic variation normalization and log2 transformed

> gse <- getGEO(‘GSE41342’)

#select a subset of samples
> tmp <- gse[[1]]
> eset <- tmp[ , tmpt$characteristics_ch1.2 %in% c(“protocol: no surgery”, “protocol: DMM surgery”) & tmp$characteristics_ch1.4 %in% c(“age: 12 weeks”, “age: 20 weeks”)]

#create groups
> f <- factor(as.character(eset$characteristics_ch1.2))
> design <- model.matrix(~f)   #i don’t understand fully what this command does 

#compare differences in expression
> fit <-eBayes(lmFit(eset, design)

#select genes that have a meaningful significance
> selected <- p.adjust(fit$p.value[ , 2] < 0.05
> esetSel <- eset[selected,]

#create the heatmap
heatmap.2(exprs(esetSel), col=redgreen(75), scale=“none",
           key=TRUE, symkey=FALSE, density.info="none", trace="none", cexRow=0.5)

sessionInfo()
R version 3.0.2 (2013-09-25)
Platform: x86_64-apple-darwin10.8.0 (64-bit)

locale:
[1] pt_PT.UTF-8/pt_PT.UTF-8/pt_PT.UTF-8/C/pt_PT.UTF-8/pt_PT.UTF-8

attached base packages:
[1] parallel  stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
[1] gplots_2.12.1      limma_3.18.7       GEOquery_2.28.0    Biobase_2.22.0    
[5] BiocGenerics_0.8.0

loaded via a namespace (and not attached):
[1] bitops_1.0-6       caTools_1.16       gdata_2.13.2       gtools_3.1.1      
[5] KernSmooth_2.23-10 RCurl_1.95-4.1     tools_3.0.2        XML_3.95-0.2 

Thank you for your help

António



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