How to filter genes inside a normalized count data file based on p-adjust value?

Question

[Amr]

How to filter genes inside a normalized count data file based on p-adjust value?

I want to add a filter to only take the genes under specific p-adjust value?

Here are the normalization steps:

dds <- DESeqDataSetFromMatrix(countData = countdata,colData = coldata,design= ~ condition)
dds <- DESeq(dds)
count_data_normalized <- counts(dds, normalized=TRUE)

[Basti]

Based on which p-values ? I can't see any differential expression analysis here

[Amr]

Do I have to extract the results table from results function: results(dds), then I make filtration based on p-adjust value? But If I do that, then how can I extract again the genes under specific p-value?

[Basti]

If you want to select genes from a differential analysis results, yes you should use results() but pay attention to your study design to extract the contrast you need. Then you can use dplyr and the filter function to retain the genes which meet your specific criteria

[Amr]

So, use results command to extract the p-adjust, then I need to select the filtered genes to pick them only from the count data normalized file, right? If so then how? by left_join? Thanks a lot @Basti

[Basti]

When you have the filtered genes, just select from counts the corresponding rownames

[Amr]

But the genes will gonna be several as the data already have 24,000 genes

[Basti]

Please clarify your problem, and explain the desired output