Deseq2 unsupervised analysis (heatmap row scaling or none?)
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@jarod_v6liberoit-6654
Last seen 5.1 years ago
Italy

I would like to do a unsupervised heatmap using deseq2 counts.

If I use :

 

topVarGenes <- order(rowVars(assay(rld)),decreasing=TRUE)[1:1000]
mat <- assay(rld)[ topVarGenes, ]
mat <- mat - rowMeans(mat)
pheatmap(mat, annotation_col=df)

 

Which is the right way to do? Using scale="row" or scale="none"?

 

 

deseq2 pheatmap • 3.9k views
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What do you mean by 'right way'?

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I mean what is the way to perform the unsupervised analysis starting from DeSeq2 package.

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@mikelove
Last seen 3 hours ago
United States

We recommend scale="none" in the workflow.

Here is a previous post where I give some rationale for this decision:

A: Biclustering Normalizing by Row in Heatmap of DESeq2

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@jarod_v6liberoit-6654
Last seen 5.1 years ago
Italy

Thanks ! I read the that but I have this situation:

topVarGenes <- order(-rowVars(assay(rld)))[0:1000]

 

mat <- assay(rld)[ topVarGenes, ]
mat<- mat - rowMeans(mat)
colnames(mat) <- paste0(metadata$CONDITION,"-",metadata$ID)

#draw heatmap
nome<- "Image_analisi/Unsupervised_1000highvariation.png"
pheatmap(mat,method="complete",main = "Unsupervise 1000 genes ", show_rownames = F, color=color1,annotation_legend = TRUE, legend=T, cluster_cols=TRUE,file=nome)

 

If I use scale none or scale row  I have a radical change of the cluster of my groups :

Here you have the images: http://imgur.com/a/uxxx8 The first one is the use scale=none e scale row. In the first case seem I have all my data is down-regulate...

 

 

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The color mapping is not good here for two reasons: 1/12 men are color blind and red/green is very difficult to distinguish The 0 value is not set to black If you have more questions on pheatmap or plotting but not related to DESeq2 functions feel free to post them as new questions but without the DESeq2 tag.
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