Hi, I have normalized counts data and DESeq2 result file (including log2FC and Padj values) of each sample. And I want to generate a heatmap of significantly differentially expressed genes (FDR<0.05; log2FC>2) in R studio. However, I could not be sure how to filter the significantly expressed genes from only these files and unfortunately, I do not have the chance to re-run the DEseq2 analysis. Can anyone give me some suggestions on data filtering and scaling options to generate heatmap?
From the DESeq2 manual, I read that VST or rlog transformation can be done before heatmap, but since I already have the normalized count data I guess converting them into Z-score can be another option? Any suggestion will be appreciated.