Hi, you are right thanks. I changed it to 16 samples.

So there is a post that is almost similar to my design (here). It mentions that it is good to have all the samples at the same time to estimate the variance across many more degrees of freedom.

I have created one other group so in total I have 3 cols: sex, condition, group (condition_group).

Then I have this design:

dds <- DESeqDataSetFromHTSeqCount( sampleTable = sampleTable, directory = directory, design= ~group)
dds <- DESeq(dds)

contrast_male <- c("group", "treated_male", "untreated_male")
res_male <- results(dds, contrast = contrast_male, alpha = 0.05)
contrast_female <- c("group", "treated_female", "untreated_female")
res_female <- results(dds, contrast = contrast_female, alpha = 0.05)    
class(res_male)

resultsNames(dds)
>> [1] "Intercept"
>> [2] "group_treated_male_vs_untreated_female"
>> [3] "group_untreated_female_vs_treated_female"
>> [4] "group_untreated_male_vs_treated_female"

res_male    
>> log2 fold change (MAP): group treated_male vs untreated_male
>> Wald test p-value: group treated_male vs untreated_male
>> DataFrame with 21971 rows and 6 columns

my question is, why I do not have the right comparisons in the resultsName ( it does not even have treated_male vs untreated_male)? eventhough the res_male show that the comparison is treated_male vs untreated_male