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!

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)

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

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