*Hi,*
*while I try to analysis my data as the following ,I faced some problem
with (heatmap()):*
> dat<-ReadAffy()
> dat
AffyBatch object
size of arrays=1164x1164 features (20 kb)
cdf=HG-U133_Plus_2 (54675 affyids)
number of samples=10
number of genes=54675
annotation=hgu133plus2
notes=
> dat2<-rma(dat)
Background correcting
Normalizing
Calculating Expression
> dat.m<-exprs(dat2)
*The normalized data can be so large that clustering all the genes (or*
*arrays) becomes impossible. Clustering about 23000 genes takes about 1GB
of memory, and clustering 54675 genes would consume about more than 4 GBs
ofmemory, and would not be feasible on a standard Windows workstation.*
*So I tried to sample the data, and this sample*
*is then clustered. This should convey approximately the same information
asthe clustering of the whole dataset:*
> n<-1:nrow(dat.m)
> n.s<-sample(n, nrow(dat.m)*0.1)
> dat.sample<-dat.m[n.s,]
> library(amap)
> clust.genes<-hcluster(x=dat.sample, method="pearson",
+ link="average")
> clust.arrays<-hcluster(x=t(dat.sample), method="pearson",
+ link="average")
*The sample size is here 10% of the original dataset.*
Ok, then I tried to visualizing the clustering results as a heatmap:
> heatcol<-colorRampPalette(c("Green", "Red"))(32)
> heatmap(x=as.matrix(dat.m), Rowv=as.dendrogram(clust.genes),
+ Colv=as.dendrogram(clust.arrays), col=heatcol)
*Error in .heatmap(x=as.matrix(dat.m),
Rowv=as.dendrogram(clust.genes), :**row dendrogram ordering gave
**index of wrong length*
*Was that sample of the data make an error with heatmap()??*
*Cheers,*
*Tahani.*
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