As per Lila, if you follow the DESeq2 vignette (see the link in Lila's answer), then you will learn a lot about how you can achieve what you are aiming to do.
My recommendation is to conduct a differential expression analysis between your positive and negative treatments - this will produce a table of test statistics (p-values, fold changes, etc). With this table of test statistics, you can identify the genes / variables that are statistically significantly differentially expressed between your positive and negative treatments. From this, you can obtain a list of genes that are differentially expressed.
With the list of differentially expressed genes, you can subset your matrix such that the matrix only includes these genes. Then, you can create a heatmap, which should show separation between your positive and negative treatments.