Question: Deseq2 supervised heatmap
0
4.4 years ago by
aristotele_m30
Italy
aristotele_m30 wrote:

I want to create a supervised heatmap for the differential expression data obtained from rnaseq analysis using deseq2.

I'm not able to see the up and down genes cluster  expression  even if I plot only differential expresion data results.

dds <- DESeq(dds)
res<-results(dds)
resOrdered <- res[order(res\$padj),]
head(resOrdered)

select_genes<-rownames(subset(resOrdered, padj < 0.1))

pheatmap(assay(rld)[ select_genes,],cluster_rows =F)

heatmap.2(assay(rld)[ select_genes,] ,density.info = "none",symm=F,Colv =T,trace="none")

If I want to sho better the upregolted gene and downregulate what can I do?

thanks so much!


deseq2 supervised • 5.9k views
ADD COMMENTlink
modified 4.4 years ago • written 4.4 years ago by aristotele_m30

Are you using a simple design or one with multiple factors?

Do the samples cluster if you choose only the top 10 genes? top 20 genes?

ADD REPLYlink written 4.4 years ago by Michael Love24k

thanks so much,

I have one sample design ( treated vs control) .

ADD REPLYlink written 4.4 years ago by aristotele_m30

Did you try my second suggestion: to see if clustering works with the top genes?

ADD REPLYlink written 4.4 years ago by Michael Love24k
Answer: Deseq2 supervised heatmap
0
4.4 years ago by
aristotele_m30
Italy
aristotele_m30 wrote:

Thanks so much for you help!

If I use only 10 or 20 genes work really well.

I have problem on the visualization plot. I mean  if I use pheatmap I can't see wit the colors all red on the dirst group and all green in the second group. on heatmap.2 gave me the right results. Even if I use this code I can' obtain a very clear red and green. Where I did wrong?

mat<-assay(rld)[select_gene,]

mat<-mat-rowMeans(mat)

heatmap(mat,cluster_rows =F)

ADD COMMENTlink written 4.4 years ago by aristotele_m30
Answer: Deseq2 supervised heatmap
0
4.4 years ago by
Sean Davis21k
United States
Sean Davis21k wrote:

Try adding scale="row" to heatmap.2 or pheatmap.

ADD COMMENTlink written 4.4 years ago by Sean Davis21k
Answer: Deseq2 supervised heatmap
0
4.4 years ago by
aristotele_m30
Italy
aristotele_m30 wrote:

This is the results o differential expression.:

out of 24250 with nonzero total read count
adjusted p-value < 0.1
LFC > 0 (up)     : 123, 0.51%
LFC < 0 (down)   : 163, 0.67%
outliers [1]     : 0, 0%
low counts [2]   : 1213, 5%
(mean count < 3.1)
[1] see 'cooksCutoff' argument of ?results
[2] see 'independentFiltering' argument of ?results

ADD COMMENTlink modified 4.4 years ago • written 4.4 years ago by aristotele_m30
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