Creating Heatmaps Of Diffrentially Expressed Genes In Agilent Two-Color Array Analysis

Question

[Ly]

Hi. I am trying to create a heatmap from my data after I have analyzed it using Limma. I can get a list of genes that are shown to be significant in my analysis but would like to locate the same genes in my original data matrix to make a heat map of it. This is what I've done (below) but I can't seem to get the legions right. I would like to have the row names be the gene and rename the column. Any help to this problem will be much appreciated. Thanks in advance.

targets<-readTargets("HxMtargets.txt")
RG <- read.maimages(targets,source="agilent",columns= list( R = "rMeanSignal", G = "gMeanSignal", Rb = "rBGUsed", Gb = "gBGUsed", Rb.real = "rBGMeanSignal", Gb.real = "gBGMeanSignal"), annotation = c("FeatureNum","Row","Col","ProbeName","ControlType","GeneName", "Description","SystematicName"))
MA<-normalizeWithinArrays(RG,method="loess")
f<-factor(targets$Cy3,levels=c("Control","Twowks","Tumor"))
design<-model.matrix(~0+f)
colnames(design) <- c("Control","Twowks","Tumor")
fit<-lmFit(MA, design)
contrast.matrix<-makeContrasts(Control,Twowks,Tumor,Tumor-Control,Tumor-Twowks, Twowks-Control, levels=design)
fit2<-contrasts.fit(fit,contrast.matrix)
fit2<-eBayes(fit2)
C.top<-as.numeric(rownames(topTable(fit2, coef=1,n=50)))
heatmap(MA$M[C.top,])

Answer 1

[Sean Davis]

Take a look at the gplots package, for example, at the heatmap.2 function. Something like this should give you an idea:

d = matrix(rnorm(26*26),ncol=26)
heatmap.2(d,labRow=letters[1:26],labCol=letters[1:26])

You'll just substitute your MA$M[C.top,], labRow=genenames[C.top], and labCol=samplenames. heatmap.2 has many tweaks for better visualization, so you may need to play a bit to get things just right.

[Ly]

Thanks you so much Sean! I did try this with some modifications of my own and it worked perfectly! Again, thank you.

[Istvan Albert]

Hi Ly, if you like the answer upvote and accept it.

[Vasu]

Hi Sean,

Like the above question even I'm facing the same problem to get heatmap of differential expressed genes. Could you please hep me. I'm working on Human Gene 2.0 ST array. I have used "xps" package for the analysis.

scheme.exon <- import.exon.scheme("Scheme",filedir=scmdir,layoutfile=paste(libdir,"HuGene-2_0-st.clf",sep="/"),schemefile=paste(libdir,"HuGene-2_0-st.pgf",sep="/"),probeset=paste(anndir,"HuGene-2_0-st-v1.na35.hg19.probeset.csv",sep="/"),transcript=paste(anndir,"HuGene-2_0-st-v1.na35.hg19.transcript.csv",sep="/"),verbose=TRUE)

##Reading CEL Info
#Import CEL-files by giving the path where all .CEL files are present

celfiles <- dir(path = "D:/GeneST_Analyse/ProjectName/CELfiles", pattern = "*.CEL$", all.files = FALSE, full.names = FALSE, recursive = FALSE, ignore.case = FALSE)
data.exon <- import.data(scheme.exon,"tmp_data_exon",filedir=rootdir,celfiles=celfiles,celdir=celdir,verbose=FALSE)

unlist(treeNames(data.exon))

[1] "X_8__HuGene_2_0_st_.cel" "E__HuGene_2_0_st_.cel"  
[3] "GG7__HuGene_2_0_st_.cel" "J__HuGene_2_0_st_.cel"  
[5] "O__HuGene_2_0_st_.cel"   "T__HuGene_2_0_st_.cel"

data.rma <- rma(data.exon, "tmp_exonRMA", filedir=rootdir, verbose=FALSE, exonlevel="affx+core", option="transcript", background="antigenomic")

>data.rma

UNIT_ID   UN       X       E       GG7     J     O
0      17127159 353.568 335.295 221.717 815.654 684.85
1      17127161 11.0842 7.01459 7.33511 11.2121 12.6268
2      17127163 221.647 226.774 136.274 431.32  392.533
3      17127165 5.02182 3.41172 4.12834 6.90306 4.91183

unifltr <- UniFilter(foldchange=c(1.5,"both"), unifilter=c(0.05,"pval"))

rma.ufr <- unifilter(data.rma, "tmp_exonUnifilter", filedir=rootdir , filter=unifltr, group=c("GrpA","GrpA","GrpA","GrpB","GrpB","GrpB"), xps.fltr=rma.pfr, verbose=FALSE)

tmp2 <- validData(rma.ufr)

tmp2 has differential expressed genes.

UN          ID    St      M1    M2       SE    DOF  PV        PA            FC
17127159    0   -5.9    297.3   765.7   0.22    4   0.003   0.00389231  2.57536
17127163    2   -3.87   189.914 492.307 0.3548  4   0.0179  0.01795     2.59226
17127167    4   -3.8908 339.136 855.276 0.3429  4   0.0176  0.017       2.52192
17127171    6   -3.922  390.44  986.365 0.340   4   0.0172179   0.01721 2.52627
17127175    8   -4.715  536.072 1210.65 0.2492  4   0.00920158  0.00920 2.258

How can I get a heatmap for this?