**0**wrote:

Hi All,

I've run DESeq2 on my counts comparing two conditions, treated vs untreated. I have my dds object and have generated my vsd object using the command:

```
vsd <- vst(dds, blind = FALSE)
```

then plotted my PCA using:

```
plotPCA(vsd, intgroup = "condition", ntop = 500)
```

However, I'd like to produce another plot using just a subset, which is those genes I identified as DE (padj < 0.05). My problem is, when I try to extract a subset from the vsd data using:

```
de <- rownames(res[res$padj<0.05 & !is.na(res$padj), ])
de_mat <- assay(vsd)[de,]
```

Then try to use this object to plot the PCA:

```
plotPCA(de_mat, intgroup = "condition", ntop = 500)
```

I receive the error message:

```
Error in (function (classes, fdef, mtable) :
unable to find an inherited method for function ‘plotPCA’ for signature ‘"matrix"’
```

Which makes sense because de_mat is a matrix and vsd is not. Can anyone help me with another way to extract my subset of genes from the dds/ vsd object so I can use the subsequent object to plot a PCA?

I need to confirm, via PCA, that this subset does indeed discriminate between the two groups sufficient to justify my downstream analyses. My PCA using the full gene set shows mixing of the groups and it would be great to be able to justify using a great visual like a PCA for just the DE genes at this point, so that I can show clear separation of the groups.

I greatly appreciate all help in advance. If anyone has ideas on other visuals, I'm open to those as well. I've already covered heatmaps and volcano plots, though; it's just that my PI really likes the idea of the DE genes only PCA.