Hello! I am analyzing my RNA-seq data using the DESeq2 method. I am using the following code to plot the 50 most differentially expressed genes in my database, but in my biological triplicate, I have one sample that acts as an outlier in the expression of some genes but looks congruent with the expression of the other replicates when I consider a large number of genes. !. I noticed that these "outliers" are not considered significant in the results (not significant padj) so they just come out in the heatmap. I am wondering if it is possible to create an heatmap or other plots using the csv result file, generated after the command res <- result(dds). The csv file contains the genes ID, the baseMean, the log2FoldChange, the lfcSE, the stat, the pvalue and the padj. I would like to create a plot using, for example, the 50 genes with the lowest padj score. Could you please suggest if there is a code for this? Or a reference that explains how to plot the results?

I apologize if my question is not correct or if I am not using the proper words, I started recently to use DESeq2 and I am not so proficient in coding, so I am a beginner in the RNAseq analysis.

Thank you for your time and your help.

Code should be placed in three backticks as shown below

```# select the 50 most differentially expressed genes topVarGenes <- head(order(rowVars(assay(rld)), decreasing = TRUE), 50)

mat <- assay(rld)[ topVarGenes, ] mat <- mat - rowMeans(mat) anno <- as.data.frame(mat)

library(ComplexHeatmap) library(ggplot2) f <- Heatmap(mat, cluster_rows = T, cluster_columns = F, column_labels = colnames(anno), name = "Z-score") png('Heatmap_1oo.png', res = 250, width = 1000, height = 3000) print(f) dev.off()

```

For me the point of a heatmap is to show exactly this kind of sample variation and I don’t recommend using it just to show the information in the results table.