I went through the vignette about interaction terms and would like to understand if I am applying interaction terms correctly and biologically, if I am extracting the correct the terms. Here is the example code from DESeq2 R documentation for **two conditions (A, B) and three genotypes (I,II,III)**. Let A and B be 2 conditions as: **placebo and treatment** respectively and in case of genotype: **I is KO (where, gene X is knock out), II is WT and III is Tg (where, extra copy of gene X is present).** 

    > dds <- makeExampleDESeqDataSet(n=100,m=18)
    > dds$genotype <- factor(rep(rep(c("I","II","III"),each=3),2))
    > dds
    class: DESeqDataSet 
    dim: 100 18 
    metadata(1): version
    assays(1): counts
    rownames(100): gene1 gene2 ... gene99 gene100
    rowData names(3): trueIntercept trueBeta trueDisp
    colnames(18): sample1 sample2 ... sample17 sample18
    colData names(2): condition genotype
    > dds$genotype <- factor(rep(rep(c("I","II","III"),each=3),2))
    > design(dds) <- ~ genotype + condition + genotype:condition
    > dds <- DESeq(dds)
    estimating size factors
    estimating dispersions
    gene-wise dispersion estimates
    mean-dispersion relationship
    final dispersion estimates
    fitting model and testing
    > resultsNames(dds)
    [1] "Intercept"              "genotype_II_vs_I"       "genotype_III_vs_I"     
    [4] "condition_B_vs_A"       "genotypeII.conditionB"  "genotypeIII.conditionB"

If we go through each and every terms under `resultsName(dds)` then:
> `genotype_II_vs_I` will be the comparison between WT and KO across treatment and placebo,

> `genotype_II_vs_I` will be the comparison between Tg and KO across treatment and placebo,

> `condition_B_vs_A` will be the comparison between treatment vs control for genotype I,

> `genotypeII.conditionB` will be the interaction effect of WT and treatment across genotype III vs genotype I.

> `genotypeIII.conditionB` will be the interaction effect of WT and treatment across genotype III vs genotype I.

I am interested to get the list of genes that are affected by both gene X and treatment ? How can I better model all the effects like treatment and genotype effect on Tg/WT vs KO ?

So you're interested in condition B vs A, taking care of interaction between genotype II vs I (KO over WT) ? Then it should be `genotypeII.conditionB` result.
